It is argued that Maximum Likelihood Estimation (MLE) is wrong, both conceptually and in terms of results it produces (except in two very special cases, which are discussed). While the use of MLE can still be justified on the basis of its practical performance, we argue there are better estimation methods that overcome MLE's empirical and philosophical shortcomings while retaining all of MLE's benefits.

Maximum Parsimony (MP) and Maximum Likelihood (ML) are two methods for evaluating which phlogenetic tree is best supported by data on the characteristics of leaf objects (which may be species, populations, or individual organisms). MP has been criticized for assuming that evolution proceeds parsimoniously -- that if a lineage begins in state i and ends in state j, the way it got from i to j is by the smallest number of changes. MP has been criticized for (...) needing to assume some model or other of the evolutionary process even though biologists often do not know what that process really is. This paper critically evaluates both criticisms. (shrink)

Michael Weisberg’s account of scientific models concentrates on the ways in which models are similar to their targets. He intends not merely to explain what similarity consists in, but also to capture similarity judgments made by scientists. In order to scrutinize whether his account fulfills this goal, I outline one common way in which scientists judge whether a model is similar enough to its target, namely maximum likelihood estimation method. Then I consider whether Weisberg’s account could capture the (...) judgments involved in this practice. I argue that his account fails for three reasons. First, his account is simply too abstract to capture what is going on in MLE. Second, it implies an atomistic conception of similarity, while MLE operates in a holistic manner. Third, Weisberg’s atomistic conception of similarity can be traced back to a problematic set-theoretic approach to the structure of models. Finally, I tentatively suggest how these problems might be solved by a holistic approach in which models and targets are compared in a non-set-theoretic fashion. (shrink)

Background: Previous studies assessing students’ learning outcomes and identifying contributing factors have often dwelt on the cognitive domain. Furthermore, school evaluation decisions are often made using scores from cognitive-based tests to rank students. This practice often skews evaluation results, given that education aims to improve the three learning domains. This study addresses this gap by assessing the contributions of four students’ input to their cognitive, affective and psychomotor skills (CAPs). Methods: A cross-section of senior secondary class II students (n = (...) 870), sampled through the multistage procedure, participated in a physical survey. Students’ Inputs Questionnaire (STIQ) and Learning Outcomes Questionnaire (LOQ) were used for data collection. Based on data obtained from a pilot sample (n = 412), principal axis factoring (PAF) was performed to assess the internal structure of the instruments following an oblique rotation. The KMO value of sampling adequacy were 0.88 and 0.94, while the Bartlett’s test of sphericity were significant χ2 (253) = 5,010; p < 0.001 and χ2 (105) = 3693.38, p < 0.001 for the STIQ and LOQ, respectively. Confirmatory factor analysis was used to assess the models’ acceptability based on the maximum likelihood estimation technique. The main study used hierarchical linear regression for data analysis. Results: Findings indicated that innate ability, health, motivation and social capital relatively and cumulatively predicted students’ overall, cognitive, affective and psychomotor learning outcomes. The proportion of variance explained by the predictors increased at different levels of the models with the addition of new variables. Students’ social capital reduced the effect of students’ innate ability regardless of their motivation and health status. Conclusion/implication: This study has provided evidence that the four students’ inputs are crucial predictors of their learning outcomes in the three domains. This result is helpful for school management to provide services aimed at improving the school climate for students’ motivation and social capital. The result can provide policymakers with a proper understanding of the constituents of learning outcomes and how policies can be aligned to secure quality student inputs for maximum productivity in education. (shrink)

I give a pedagogical derivation of the Cramer-Rao Bound, which gives a lower bound on the variance of estimators used in statistical point estimation, commonly used to give numerical estimates of the systematic uncertainties in a measurement.

heart attack analysis & prediction dataset is a major cause of death worldwide. Early detection and intervention are essential for improving the chances of a positive outcome. This study presents a novel approach to predicting the likelihood of a person having heart failure using a neural network model. The dataset comprises 304 samples with 11 features, such as age, sex, chest pain type, Trtbps, cholesterol, fasting blood sugar, resting electrocardiogram results, maximum heart rate achieved, exercise-induced angina, oldpeak, ST_Slope, (...) and HeartDisease. A neural network model with four layers (1 input, 2 hidden, 1 output) was trained on the dataset and achieved an accuracy of 88% and an average error of 0078296. The most influential factors in heart failure prediction were found to be oldpeak, ST_Slope, sex, fastingBS, chestPainType, exerciseAngina, cholesterol, restingBP, maxHR, restingBP, and age. This study provides a valuable tool for early detection and intervention of heart failure, thereby contributing to the field of health and medicine. (shrink)

An important problem with machine learning is that when label number n>2, it is very difficult to construct and optimize a group of learning functions, and we wish that optimized learning functions are still useful when prior distribution P(x) (where x is an instance) is changed. To resolve this problem, the semantic information G theory, Logical Bayesian Inference (LBI), and a group of Channel Matching (CM) algorithms together form a systematic solution. MultilabelMultilabel A semantic channel in the G theory consists (...) of a group of truth functions or membership functions. In comparison with likelihood functions, Bayesian posteriors, and Logistic functions used by popular methods, membership functions can be more conveniently used as learning functions without the above problem. In Logical Bayesian Inference (LBI), every label’s learning is independent. For Multilabel learning, we can directly obtain a group of optimized membership functions from a big enough sample with labels, without preparing different samples for different labels. A group of Channel Matching (CM) algorithms are developed for machine learning. For the Maximum Mutual Information (MMI) classification of three classes with Gaussian distributions on a two-dimensional feature space, 2-3 iterations can make mutual information between three classes and three labels surpass 99% of the MMI for most initial partitions. For mixture models, the Expectation-Maxmization (EM) algorithm is improved and becomes the CM-EM algorithm, which can outperform the EM algorithm when mixture ratios are imbalanced, or local convergence exists. The CM iteration algorithm needs to combine neural networks for MMI classifications on high-dimensional feature spaces. LBI needs further studies for the unification of statistics and logic. (shrink)

Heart failure is a major cause of death worldwide. Early detection and intervention are essential for improving the chances of a positive outcome. This study presents a novel approach to predicting the likelihood of a person having heart failure using a neural network model. The dataset comprises 918 samples with 11 features, such as age, sex, chest pain type, resting blood pressure, cholesterol, fasting blood sugar, resting electrocardiogram results, maximum heart rate achieved, exercise-induced angina, oldpeak, ST_Slope, and HeartDisease. (...) A neural network model with four layers (1 input and 1 output) was trained on the dataset and achieved an accuracy of 90% and an average error of 0.009. The most influential factors in heart failure prediction were found to be oldpeak, ST_Slope, sex, fastingBS, chestPainType, exerciseAngina, cholesterol, restingBP, maxHR, restingBP, and age. This study provides a valuable tool for early detection and intervention of heart failure, thereby contributing to the field of health and medicine. (shrink)

RESUMO A bovinocultura sempre esteve atrelada ao desenvolvimento do Brasil e, pensando no avanço, as exigências da máxima eficiência nos sistemas de criação foi pautada na forma de como conseguir realizar a reprodução de bovinos com ênfase na eficiência econômica e reprodutiva. O objetivo deste trabalho é elucidar as principais biotecnologias que auxiliam na maior produtividade reprodutiva de bovinos. Dessa forma, o estudo foi realizado usando artigos do banco de dados do Google acadêmico e SciELO, além de livros do acervo (...) pessoal e sites oficiais. Com o manejo reprodutivo aplicado na bovinocultura, é possível identificar pontos a serem melhorados e implantação de práticas que auxiliam no incremento da eficiência reprodutiva como a estação de monta, que concentra a fertilização dos animais em uma determinada época do ano, o uso do índice de escore corporal, o qual consegue determinar a viabilidade da vaca a ser fertilizada, e a identificação da idade a puberdade, na qual a novilha com 60% de peso vivo quando adulta pode estar apta para reprodução, indicando que a nutrição é um fator importante para reduzir o intervalo entre partos, bem como na indução da precocidade, que ainda pode ser maximizada por uso de bioestimuladores. Assim como a implantação do uso de biotecnologias, que podem adicionar aos planteis, indivíduos geneticamente superiores, saudáveis e eficientes. Dentre as biotecnologias, a inseminação artificial é a mais usada no Brasil, com capacidade de fertilizar vacas com sêmen de touros de genética superior, nacional ou importado. Podem ser citadas ainda as técnicas de transferência de embriões e produção in vitro de embriões como tecnologias a serviço do desenvolvimento da eficiência reprodutiva. A utilização de protocolos hormonais no ciclo estral objetiva a sincronização do estro das vacas para facilitar o emprego das biotecnologias. São vários os protocolos usados para essa finalidade, sendo Ovsynch a base de GnRH e prostaglandina com até 50% de eficácia, protocolos à base de estradiol e progesterona com eficácia de até 86,6%, e protocolos que usam gonadotrofina coriônica equina (eCG), indicados para animais magros por condicionar maior diâmetro folicular, o qual é relacionado com aumento na taxa de prenhez. Dessa maneira, as práticas e tecnologias citadas neste estudo são usadas na reprodução assistida de bovinos. PALAVRAS-CHAVE: Criopreservação. Estro. Gestação. Hipófise. Nutrição. ABSTRACT Cattle farming has always been linked to Brazil’s development and, thinking about advancement, the requirements for maximum efficiency in breeding systems was based on how to achieve the reproduction of cattle with an emphasis on economic and reproductive efficiency. The objective of this work is to elucidate the main biotechnologies that help in the greater reproductive productivity of cattle. Thus, the study was done using articles from the Academic Google and SciELO databases, as well as books from the personal collection and official websites. With the reproductive management applied in cattle farming, it is possible to identify points to be improved and implement practices that help to increase reproductive efficiency, such as the breeding season, which concentrates the fertilization of animals at a certain time of year, use of the body score index, which can determine the viability of the cow to be fertilized, identification of age at puberty, in which the heifer with 60% live weight as an adult may be suitable for reproduction, indicating that nutrition is an important factor in reducing the interval between births, as well as in inducing precocity, which can still be maximized by the use of biostimulators. As well as the implementation of the use of biotechnology, which can add genetically superior, healthy and efficient individuals to the breeding stock. Among the biotechnologies, artificial insemination is the most used in Brazil, with the capacity to fertilize cows with superior genetic bull semen, whether national or imported. Embryo transfer techniques and in vitro embryo production can also be cited as technologies in the service of the development of reproductive efficiency. The use of hormonal protocols in the estrous cycle aims at synchronizing the estrus of cows to facilitate the use of biotechnologies. There are several protocols used for this purpose, with Ovsynch being based on GnRH and prostaglandin with up to 50% efficacy, protocols based on estradiol and progesterone with efficacy of up to 86.6%, and protocols that use equine chorionic gonadotropin (eCG), indicated for lean animals because they condition larger follicular diameter, which is related to an increase in the pregnancy rate. Thus, the practices and technologies mentioned in this study can help the assisted reproduction of cattle. KEYWORDS: Cryopreservation. 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Likelihoodism is the view that the degree of evidential support should be analysed and measured in terms of likelihoods alone. The paper considers and responds to a popular criticism that a likelihoodist framework is too restrictive to guide belief. First, I show that the most detailed and rigorous version of this criticism, as put forward by Gandenberger (2016), is unsuccessful. Second, I provide a positive argument that a broadly likelihoodist framework can accommodate guidance for comparative belief, even when objectively well-grounded (...) prior probabilities are not available. As I show, the shift from non-relational to comparative probabilities opens up a new space for addressing the belief guidance problem for likelihoodism. (shrink)

An adequate account of laws should satisfy at least five desiderata: it should provide a unified account of laws and chances, it should yield plausible relations between laws and chances, it should vindicate numerical chance assignments, it should accommodate dynamical and non-dynamical chances, and it should accommodate a plausible range of nomic possibilities. No extant account of laws satisfies these desiderata. This paper presents a non-Humean account of laws, the Nomic Likelihood Account, that does.

An important suggestion of objective Bayesians is that the maximum entropy principle can replace a principle which is known to get into paradoxical difficulties: the principle of indifference. No one has previously determined whether the maximum entropy principle is better able to solve Bertrand’s chord paradox than the principle of indifference. In this paper I show that it is not. Additionally, the course of the analysis brings to light a new paradox, a revenge paradox of the chords, that (...) is unique to the maximum entropy principle. (shrink)

Since the release of OpenAI's ChatGPT, the world has entered a race to develop more capable and powerful AI, including artificial general intelligence (AGI). The development is constrained by the dependency of AI on the model, quality, and quantity of training data, making the AI training process highly costly in terms of resources and environmental consequences. Thus, improving the effectiveness and efficiency of the AI training process is essential, especially when the Earth is approaching the climate tipping points and planetary (...) boundaries. It is evident that AI can function better when trained to mimic certain human mental processes. Based on insights from quantum mechanics and the informational entropy-based notion of value, we suggest AI developers can enhance the AI training processes' effectiveness and efficiency by creating and implementing parameter systems that are capable of effectively assigning probabilities to informational quanta. Such systems can help reduce entropy within the system, which lowers the energy required for data storage and processing while decreasing the likelihood of information loss during training. Successfully applying the concept of information entropy-based value in AI development will be crucial for advancing generative AI and achieving AGI in a sustainable manner. (shrink)

According to a bits generation technique, that is, bits can only take a binary value of 0 in the absence of wave function collapse and 1 when wave function collapse occurs, that is, regardless of the value random in which the collapse of the wave function occurs that in the past caused the development of an alternative technique of classic bits to be renounced and remains currently an impossibility in normal science, through series of quantum entanglements, using BCD, EBCDIC or (...) ASCII coding standard in computing, data are teleported surpassing c, from a sender to a receiver, theoretically placed at any distance. This technique is a new discovery with theoretical foundation in the work “Superluminal Data Transmission supported by Quantum Entanglement” (1) by this author, stored, since April 2023, as a preprint, in the ResearchGate, and Philpapers repositories, and pending implementation by communications engineering in a longterm future. In this work it is unequivocally established that the maximum speed c for this type of transmission is false, causing critical break with Relativity. This new technique, unlike the one presented in my previous paper, it is a version much simpler that can be implemented according to the current state of technology, so at present the instantaneous transmission of information can be tested experimentally. (shrink)

The nationwide economic reform in 1986 transformed Vietnam from a centrally planned economy to a socialist-oriented market economy. Entrepreneurs and entrepreneurial spirits within the populace are suggested to fuel the structural changes. Despite the importance of entrepreneurship in Vietnam’s economy, studies in Vietnam mainly pay attention to the practical aspects of entrepreneurial activities and neglect the cognitive and theoretical aspects of entrepreneurship. Thus, the current study employs the information-processing perspective of the Mindsponge Theory to explore how entrepreneurs’ knowledge accumulation can (...) affect their perceived likelihood of business success. Bayesian analysis indicates that business-related experience positively affects entrepreneurs’ business success likelihood. Greater willingness/readiness to transform thinking, acting, and beliefs can improve the business success of entrepreneurs who study others’ failures carefully. However, for entrepreneurs who perceive learning from others’ failures as unnecessary, higher willingness/readiness to transform diminishes their chance of success. Based on these findings, we recommend Vietnamese entrepreneurs accumulate knowledge through experience, learning, and an open mind for better decision-making and innovation creation capabilities. However, the learning process should be selective. (shrink)

I discuss the formal implementation, interpretation, and justification of likelihood attributions in cosmology. I show that likelihood arguments in cosmology suffer from significant conceptual and formal problems that undermine their applicability in this context.

Bayesian confirmation theory is rife with confirmation measures. Zalabardo focuses on the probability difference measure, the probability ratio measure, the likelihood difference measure, and the likelihood ratio measure. He argues that the likelihood ratio measure is adequate, but each of the other three measures is not. He argues for this by setting out three adequacy conditions on confirmation measures and arguing in effect that all of them are met by the likelihood ratio measure but not by (...) any of the other three measures. Glass and McCartney, hereafter “G&M,” accept the conclusion of Zalabardo’s argument along with each of the premises in it. They nonetheless try to improve on Zalabardo’s argument by replacing his third adequacy condition with a weaker condition. They do this because of a worry to the effect that Zalabardo’s third adequacy condition runs counter to the idea behind his first adequacy condition. G&M have in mind confirmation in the sense of increase in probability: the degree to which E confirms H is a matter of the degree to which E increases H’s probability. I call this sense of confirmation “IP.” I set out four ways of precisifying IP. I call them “IP1,” “IP2,” “IP3,” and “IP4.” Each of them is based on the assumption that the degree to which E increases H’s probability is a matter of the distance between p and a certain other probability involving H. I then evaluate G&M’s argument in light of them. (shrink)

Network coding is used to improve the throughput of communication networks. In this technique, the intermediate nodes mix packets to increase the information content of each transmission. For each flow, a coding pattern is defined as a set of flows that can be coded together. Finding a suitable coding pattern is a challenge due to much complexity. In this paper, we propose an algorithm to find a suitable coding pattern in intermediate nodes by mapping this problem onto maximum-weight clique. (...) Also, we described time complexity of our algorithm in details. Simulation results show that our proposed method can achieve better performance in terms of throughput and end-to-end delay by increasing coding opportunities. (shrink)

The prospect of cognitive enhancement well beyond current human capacities raises worries that the fundamental equality in moral status of human beings could be undermined. Cognitive enhancement might create beings with moral status higher than persons. Yet, there is an expressibility problem of spelling out what the higher threshold in cognitive capacity would be like. Nicholas Agar has put forward the bold claim that we can show by means of inductive reasoning that indefinite cognitive enhancement will probably mark a difference (...) in moral status. The hope is that induction can determine the plausibility of post‐personhood existence in the absence of an account of what the higher status would be like. In this article, we argue that Agar's argument fails and, more generally, that inductive reasoning has little bearing on assessing the likelihood of post‐personhood in the absence of an account of higher status. We conclude that induction cannot bypass the expressibility problem about post‐persons. (shrink)

In this paper comparative analysis of maximum power point tracking techniques has been conducted to achieve highest magnitude of power from photovoltaic array. The algorithms proposed in this paper for extracting peak output from photovoltaic array are Perturb and Observe, Incremental Conductance, and Fuzzy Logic Control. There are some limitations with conventional converters i.e. Buck-Boost converter. When the operating voltage exceeds normal voltage as the voltage becomes high, the conventional converters fail to carry high voltage and current. Apart from (...) this the ripple contents also increase abnormally due to the large impedance in the conventional converter. Similarly these converters cannot track maximum power point faster and effectively. In that case Single Ended Primary Inductor Converter (SEPIC) is the best choice instead of the conventional buck-boost converter, which is employed with the aim of extracting maximum output from the photovoltaic array. The aim of this study is to compare three MPPT techniques under varying environmental conditions with respect to maximum power extraction and speed of tracking time. SEPIC is used instead of conventional buck-boost converter in order to achieve maximum efficiency and less ripples. Also it can track maximum power point (MPP) faster than Buck-Boost Converter. Comparative analysis of three most extensively used MPPT techniques have been conducted in Simulink/Matlab. (shrink)

Metaethical absolutism is the view that moral concepts have non-relative satisfaction conditions that are constant across judges and their particular beliefs, attitudes, and cultural embedding. If it is correct, there is an important sense in which parties of moral disputes are concerned to get the same things right, such that their disputes can be settled by the facts. If it is not correct, as various forms of relativism and non-cognitivism imply, such coordination of concerns will be limited. The most influential (...) support for absolutism comes from an argument with two related premises. According to the first premise, moral thinking and moral discourse display a number of features that are characteristically found in paradigmatically absolutist domains, and only partly in uncontroversially non-absolutist domains. According to the second, the best way of making sense of these features is to assume that absolutism is correct. This paper defends the prospect of a non-ad hoc, non-absolutist, explanation of these "absolutist" features, thus calling into question the second premise. But instead of attempting to directly explain why the moral domain displays these features, it attends to how they are partially displayed by paradigmatically non-absolutists judgments about taste and likelihood. Based on this, it proposes independently motivated general accounts of attributions of agreement, disagreement, correctness and incorrectness that can explain both why absolutist domains display all "absolutist" features and why these non-absolutist domains display some. Based on these accounts, it provides preliminary reasons to think that these features of moral discourse can be given a non-absolutist explanation. (shrink)

Extreme Permissivism is the view that a body of evidence could rationally permit both the attitude of belief and disbelief towards a proposition. This paper puts forward a new argument against Extreme Permissivism, which improves on a similar style of argument due to Roger White (2005, 2014). White’s argument is built around the principle that the support relation between evidence and a hypothesis is objective: so that if evidence E makes it rational for an agent to believe a hypothesis H, (...) then E makes it rational to believe H, for all agents. In this paper, I construct a new argument against Extreme Permissivism that appeals to a logically weaker, less demanding view about evidential support, Relational Objectivity: whether a body of evidence E is more likely if H is true than if H is false is an objective matter and does not depend on how any agent interprets the relationship between E and H. Relational Objectivity is solely concerned with the conditional probabilities called likelihoods and does not put substantive constraints on an agent’s prior and posterior credences. For this reason, the presented argument avoids the standard permissivist criticism levelled against White’s argument. (shrink)

There is a plethora of confirmation measures in the literature. Zalabardo considers four such measures: PD, PR, LD, and LR. He argues for LR and against each of PD, PR, and LD. First, he argues that PR is the better of the two probability measures. Next, he argues that LR is the better of the two likelihood measures. Finally, he argues that LR is superior to PR. I set aside LD and focus on the trio of PD, PR, and (...) LR. The question I address is whether Zalabardo succeeds in showing that LR is superior to each of PD and PR. I argue that the answer is negative. I also argue, though, that measures such as PD and PR, on one hand, and measures such as LR, on the other hand, are naturally understood as explications of distinct senses of confirmation. (shrink)

Reasons transmit. If one has a reason to attain an end, then one has a reason to effect means for that end: reasons are transmitted from end to means. I argue that the likelihood ratio (LR) is a compelling measure of reason transmission from ends to means. The LR measure is superior to other measures, can be used to construct a condition specifying precisely when reasons transmit, and satisfies intuitions regarding end-means reason transmission in a broad array of cases.

Time is a complex category not only in philosophy but also in mathematics and physics. In one thought about time, the author accidentally discovered a new way to explain and solve problems related to time dilation, such as solving the problem of Muon particle when moving from a height of 10 km to the earth’s surface, while the Muon’s lifespan is only 2.2 microseconds, or explaining Michelson-Morley experiment using the new method. In addition, the author also prove that the speed (...) of light in vacuum is the maximum speed in the universe, and discovered the red shift effect while there is no increase in distance between objects. To do this, the author has built two axioms based on the discontinuity in the motion of the object and draw two consequences along with the law of conservation of time. (shrink)

This paper investigates the degree to which information theory, and the derived uses that make it work as a metaphor of our age, can be helpful in thinking about God’s immanence and transcendance. We ask when it is possible to say that a consciousness has to be behind the information we encounter. If God is to be thought about as a communicator of information, we need to ask whether a communication system has to pre-exist to the divine and impose itself (...) to God. If we want God to be Creator, and not someone who would work like a human being, ‘creating’ will mean sustaining in being as much the channel, the material system, as the message. Is information control? It seems that God’s actions are not going to be informational control of everything. To clarify the issue, we attempt to distinguish two kinds of ‘genialities’ in nature, as a way to evaluate the likelihood of God from nature. We investigate concepts and images of God, in terms of the history of ideas but also in terms of philosophical theology, metaphysics, and religious ontology. (shrink)

Recent years have witnessed a proliferation of attempts to apply the mathematical theory of probability to the semantics of natural language probability talk. These sorts of “probabilistic” semantics are often motivated by their ability to explain intuitions about inferences involving “likely” and “probably”—intuitions that Angelika Kratzer’s canonical semantics fails to accommodate through a semantics based solely on an ordering of worlds and a qualitative ranking of propositions. However, recent work by Wesley Holliday and Thomas Icard has been widely thought to (...) undercut this motivation: they present a world-ordering semantics that yields essentially the same logic as probabilistic semantics. In this paper, I argue that the challenge remains: defenders of world-ordering semantics have yet to offer a plausible semantics that captures the logic of comparative likelihood. Holliday & Icard’s semantics yields an adequate logic only if models are restricted to Noetherian pre-orders. But I argue that the Noetherian restriction faces problems in cases involving infinitely large domains of epistemic possibilities. As a result, probabilistic semantics remains the better explanation of the data. (shrink)

The manuscript found the formula to calculate the real velocity of the earth and the maximum velocity in the universe, the values of the quantities after calculation as follows: V_earth = 1.852819296∗10^8 m/s.-- C_max = 4.8507438399∗10^8 m/s.-- In order to calculate the above results, the manuscript has built a reference frame transformation suitable for all types of motion(suitable for both linear motion and chaotic motion of the reference frame). This means that we will calculate the velocity of an object (...) without using the distance S quantity of the object. (shrink)

Logical Probability (LP) is strictly distinguished from Statistical Probability (SP). To measure semantic information or confirm hypotheses, we need to use sampling distribution (conditional SP function) to test or confirm fuzzy truth function (conditional LP function). The Semantic Information Measure (SIM) proposed is compatible with Shannon’s information theory and Fisher’s likelihood method. It can ensure that the less the LP of a predicate is and the larger the true value of the proposition is, the more information there is. So (...) the SIM can be used as Popper's information criterion for falsification or test. The SIM also allows us to optimize the true-value of counterexamples or degrees of disbelief in a hypothesis to get the optimized degree of belief, i. e. Degree of Confirmation (DOC). To explain confirmation, this paper 1) provides the calculation method of the DOC of universal hypotheses; 2) discusses how to resolve Raven Paradox with new DOC and its increment; 3) derives the DOC of rapid HIV tests: DOC of “+” =1-(1-specificity)/sensitivity, which is similar to Likelihood Ratio (=sensitivity/(1-specificity)) but has the upper limit 1; 4) discusses negative DOC for excessive affirmations, wrong hypotheses, or lies; and 5) discusses the DOC of general hypotheses with GPS as example. (shrink)

A new trend in deep learning, represented by Mutual Information Neural Estimation (MINE) and Information Noise Contrast Estimation (InfoNCE), is emerging. In this trend, similarity functions and Estimated Mutual Information (EMI) are used as learning and objective functions. Coincidentally, EMI is essentially the same as Semantic Mutual Information (SeMI) proposed by the author 30 years ago. This paper first reviews the evolutionary histories of semantic information measures and learning functions. Then, it briefly introduces the author’s semantic information G theory with (...) the rate-fidelity function R(G) (G denotes SeMI, and R(G) extends R(D)) and its applications to multi-label learning, the maximum Mutual Information (MI) classification, and mixture models. Then it discusses how we should understand the relationship between SeMI and Shannon’s MI, two generalized entropies (fuzzy entropy and coverage entropy), Autoencoders, Gibbs distributions, and partition functions from the perspective of the R(G) function or the G theory. An important conclusion is that mixture models and Restricted Boltzmann Machines converge because SeMI is maximized, and Shannon’s MI is minimized, making information efficiency G/R close to 1. A potential opportunity is to simplify deep learning by using Gaussian channel mixture models for pre-training deep neural networks’ latent layers without considering gradients. It also discusses how the SeMI measure is used as the reward function (reflecting purposiveness) for reinforcement learning. The G theory helps interpret deep learning but is far from enough. Combining semantic information theory and deep learning will accelerate their development. (shrink)

Rejection is an essential part of the scholarly publishing process, acting as a filter to distinguish between robust and less credible scientific works. While rejection helps reduce entropy and increase the likelihood of disseminating useful knowledge, the process is not devoid of subjectivity. Providing more informative rejection letters and encouraging humility among editors and reviewers are essential to enhance the efficiency of knowledge production as they help ensure that valuable scientific contributions are not overlooked.

In arguing against the likelihood of consciousness in non-human animals, Descartes advances a slippery slope argument that if thought were attributed to any one animal, it would have to be attributed to all, which is absurd. This paper examines the foundations of Thomas Willis’ comparative neuroanatomy against the background of Descartes’ slippery slope argument against animal consciousness. Inspired by Gassendi’s ideas about the corporeal soul, Thomas Willis distinguished between neural circuitry responsible for reflex behaviour and that responsible for cognitively (...) or consciously mediated behaviour. This afforded Willis a non-arbitrary basis for distinguishing between animals with thought and consciousness and those without, a methodology which retains currency for neuroscience today. (shrink)

Critics of conspiracy theories often charge that such theories are implausible because conspiracies of the kind they allege tend to fail. Thus, according to these critics, conspiracy theories that have been around for a while would have been, in all likelihood, already exposed if they had been real. So, they reason, they probably are not. In this article, I maintain that the arguments in support of this view are unconvincing. I do so by examining a list of four sources (...) recently cited in support of the claim that conspiracies tend to fail. I pay special attention to two of these sources, an article by Brian Keeley, and, especially, an article by David Grimes, which is perhaps the single “best” article in support of the idea that conspiracies tend to fail. That is, it offers the most explicit and elaborate attempt to establish this view. Further, that article has garnered significant (uncritical) attention in the mainstream press. I argue that Grimes's argument does not succeed, that the common assertion that conspiracies tend to fail remains poorly supported, and that there are good reasons to think that at least some types of conspiracies do not tend to fail. (shrink)

Patients with serious illnesses or injuries may decide to quit their medical treatment if they think paying the fees will put their families into destitution. Without treatment, it is likely that fatal outcomes will soon follow. We call this phenomenon “near-suicide”. This study attempted to explore this phenomenon by examining how the seriousness of the patient’s illness or injury and the subjective evaluation of the patient’s and family’s financial situation after paying treatment fees affect the final decision on the treatment (...) process. Bayesian Mindsponge Framework (BMF) analytics were employed to analyze a dataset of 1042 Vietnamese patients. We found that the more serious the illnesses or injuries of patients were, the more likely they were to choose to quit treatment if they perceived that paying the treatment fees heavily affected their families’ financial status. Particularly, only one in four patients with the most serious health issues who thought that continuing the treatment would push themselves and their families into destitution would decide to continue the treatment. Considering the information-filtering mechanism using subjective cost–benefit judgments, these patients likely chose the financial well-being and future of their family members over their individual suffering and inevitable death. Our study also demonstrates that mindsponge-based reasoning and BMF analytics can be effective in designing and processing health data for studying extreme psychosocial phenomena. Moreover, we suggest that policymakers implement and adjust their policies (e.g., health insurance) following scientific evidence to mitigate patients’ likelihood of making “near-suicide” decisions and improve social equality in the healthcare system. (shrink)

This paper presents a unified theory of reality, which integrates two interdependent frameworks: Cellular Primary Consciousness Theory (CPCT) and Open and Closed Systems Theory (OCST). Although CPCT and OCST can each stand as individual theories, they are, in this work, combined to form a cohesive explanation of both the mechanics and purpose of the universe. CPCT posits that consciousness is a fundamental aspect of all life, extending to even the simplest cells, rather than being an emergent property exclusive to complex (...) neural systems. Drawing upon evidence from quantum mechanics, cell biology, and systems theory, CPCT challenges traditional views on the origins of consciousness by suggesting that awareness is a universal property present from the cellular level. OCST, which forms the second component of this unified theory, examines the nature of the universe as a closed system subject to the laws of entropy. This theory explores how the universe is moving toward maximum entropy, where meaning and contrasts dissolve. However, beyond this closed system lies the realm of an open system—a domain of infinite potential that transcends the dualities and limitations of the physical universe. This open system offers a philosophical explanation for existence and the possibility of eternal meaning. Together, these two theories provide a novel and cohesive framework that addresses both the mechanics of consciousness and the ultimate purpose of the universe. The integration of CPCT and OCST bridges scientific evidence from quantum biology and systems theory with philosophical explorations of existence, presenting a comprehensive vision of reality as both a closed physical system and an open metaphysical one. This unified theory encourages a reexamination of our place in the cosmos, suggesting that beyond the observable universe lies an infinite realm of potential where consciousness and meaning endure. (shrink)

There are two competing views regarding the role of mechanistic knowledge in inferences about the effectiveness of interventions. One view holds that inferences about the effectiveness of interventions should be based only on data from population-level studies (often statistical evidence from randomised trials). The other view holds that such inferences must be based in part on mechanistic evidence. The competing views are local principles of inference, the plausibility of which can be assessed by a more general normative principle of inference. (...) Bayesianism tells us to base inferences on both the ‘likelihood’ and the ‘prior’. The likelihood represents statistical evidence. One influence on the prior probability of a hypothesis like ‘d causes x’ is mechanistic knowledge of how d causes x. Thus, reasoning about such inferences by appealing to both statistical and mechanistic evidence is vindicated by our best general theory of inference. The primary contribution of this paper is to assess the merits and weaknesses of the arguments on both sides of the debate, using the Bayesian framework. This analysis lends support to those who argue that we should base our causal inferences about interventions in part on mechanistic evidence. (shrink)

According to a common conception of legal proof, satisfying a legal burden requires establishing a claim to a numerical threshold. Beyond reasonable doubt, for example, is often glossed as 90% or 95% likelihood given the evidence. Preponderance of evidence is interpreted as meaning at least 50% likelihood given the evidence. In light of problems with the common conception, I propose a new ‘relevant alternatives’ framework for legal standards of proof. Relevant alternative accounts of knowledge state that a person (...) knows a proposition when their evidence rules out all relevant error possibilities. I adapt this framework to model three legal standards of proof—the preponderance of evidence, clear and convincing evidence, and beyond reasonable doubt standards. I describe virtues of this framework. I argue that, by eschewing numerical thresholds, the relevant alternatives framework avoids problems inherent to rival models. I conclude by articulating aspects of legal normativity and practice illuminated by the relevant alternatives framework. (shrink)

According to the view that there is moral encroachment in epistemology, whether a person has knowledge of p sometimes depends on moral considerations, including moral considerations that do not bear on the truth or likelihood of p. Defenders of moral encroachment face a central challenge: they must explain why the moral considerations they cite, unlike moral bribes for belief, are reasons of the right kind for belief (or withheld belief). This paper distinguishes between a moderate and a radical version (...) of moral encroachment. It shows that, while defenders of moderate moral encroachment are well-placed to meet the central challenge, defenders of radical moral encroachment are not. The problem for radical moral encroachment is that it cannot, without taking on unacceptable costs, forge the right sort of connection between the moral badness of a belief and that belief’s chance of being false. (shrink)

A number of theistic philosophers have recently denied that God is subject to moral and rational norms. At the same time, many theists employ epistemological and inductive arguments for the existence of God. I will argue that ‘no-norms’ theists cannot make use of such arguments: if God is not subject to norms – particularly rational norms – then we can say nothing substantive about what kind of worlds God would be likely to create, and as such, we cannot predict the (...) likelihood of any particular evidence given theism. What is more, I argue that this lack of constraint on God's creative act raises a serious sceptical challenge for no-norms theism. (shrink)

In recent papers, Peter Carruthers and others have argued that the feeling of uncertainty is not metacognitive (i.e., it is not elicited by second-order cognitive appraisals) but is elicited solely by first-order likelihood estimates—a probability account of the feeling of uncertainty. In this paper, I make a case for why a probability account is sufficient to explain neither the feeling of uncertainty nor the feeling of certainty in self-reflecting humans. I argue first that humans’ feelings of (un)certainty vary in (...) ways that their probability estimates on the matter do not, and second that probability accounts elide the essentially epistemic nature of epistemic feelings. (shrink)

Conceptual engineering is the method for assessing and improving our representational devices. On its ‘broad-spectrum’ version, it is expected to be appropriately applicable to any of our representation-involving cognitive activities, with major consequences for our whole cognitive life. This paper is about the theoretical foundations of conceptual engineering thus characterised. With a view to ensuring the actionability of conceptual engineering as a broad-spectrum method, it addresses the issue of how best to construe the subject matter of conceptual engineering and successively (...) defends the theses that conceptual engineering should be: (i) About concepts, (ii) psychologically theorised, (iii) as multiply realised functional kinds. Thereby, I claim to theoretically secure and justify the maximum scope, flexibility, and impact for the method of conceptual engineering on our representational devices in our whole cognitive life—in other words, a broad-spectrum version of conceptual engineering. (shrink)

According to a captivating picture, epistemic justification is essentially a matter of epistemic or evidential likelihood. While certain problems for this view are well known, it is motivated by a very natural thought—if justification can fall short of epistemic certainty, then what else could it possibly be? In this paper I shall develop an alternative way of thinking about epistemic justification. On this conception, the difference between justification and likelihood turns out to be akin to the more widely (...) recognised difference between ceteris paribus laws and brute statistical generalisations. I go on to discuss, in light of this suggestion, issues such as classical and lottery-driven scepticism as well as the lottery and preface paradoxes. (shrink)

What we must do is step back and take a grand view of the perspectives in order to understand it on a more particular level. If we can picture all of God’s attributes on a bar graph scale, all of God’s attributes would max out at 100% each. These attributes are always operating at 100%; at no time does any attribute diminish or decrease below 100%. However, there are times when one of His attributes shows forth more than another does, (...) but they are all operating at a maximum level. (shrink)

Many countries have adopted new triage recommendations for use in the event that intensive care beds become scarce during the COVID‐19 pandemic. In addition to establishing the exact criteria regarding whether treatment for a newly arriving patient shows a sufficient likelihood of success, it is also necessary to ask whether patients already undergoing treatment whose prospects are low should be moved into palliative care if new patients with better prospects arrive. This question has led to divergent ethical guidelines. This (...) paper explores the distinction between withholding and withdrawing medical treatment during times of scarcity. As a first central point, the paper argues that a revival of the ethical distinction between doing and allowing would have a revisionary impact on cases of voluntary treatment withdrawal. A second systematic focus lies in the concern that withdrawal due to scarcity might be considered a physical transgression and therefore more problematic than not treating someone in the first place. In light of the persistent disagreement, especially concerning the second issue, the paper concludes with two pragmatic proposals for how to handle the ethical uncertainty: (1) triage protocols should explicitly require that intensive care attempts are designed as time‐limited trials based on specified treatment goals, and this intent should be documented very clearly at the beginning of each treatment; and (2) lower survival prospects can be accepted for treatments that have already begun, compared with the respective triage rules for the initial access of patients to intensive care. (shrink)

Which rules should guide our reasoning? Human reasoners often use reasoning shortcuts, called heuristics, which function well in some contexts but lack the universality of reasoning rules like deductive implication or inference to the best explanation. Does it follow that human reasoning is hopelessly irrational? I argue: no. Heuristic reasoning often represents human reasoners reaching a local rational maximum, reasoning more accurately than if they try to implement more “ideal” rules of reasoning. I argue this is a genuine rational (...) achievement. Our ideal rational advisors would advise us to reason with heuristic rules, not more complicated ideal rules. I argue we do not need a radical new account of epistemic norms to make sense of the success of heuristic reasoning. (shrink)

Rejection is an essential part of the scholarly publishing process, acting as a filter to distinguish between robust and less credible scientific works. This study examines the advantages and limitations of the rejection mechanism through the lens of Shannon’s information theory and the theory of granular interactions thinking. We argue that while rejection helps reduce entropy and increase the likelihood of disseminating useful knowledge, the process is not devoid of subjectivity. We propose two recommendations to improve the rejection mechanism: (...) providing more informative rejection letters to guide authors and encouraging humility among editors and reviewers to minimize bias against novel ideas. These steps could enhance the efficiency of knowledge production by ensuring that valuable scientific contributions are not overlooked. (shrink)

‘Epistemic exploitation occurs when privileged persons compel marginalised knowers to educate them [and others] about the nature of their oppression’ (Berenstain, 2016, p. 569). This paper scrutinizes some of the purported wrongs underpinning this practice, so that educators might be better equipped to understand and avoid or mitigate harms which may result from such interventions. First, building on the work of Berenstain and Davis (2016), we argue that when privileged persons (in this context, educators) repeatedly compel marginalised or oppressed knowers, (...) to not only to educate them, but indeed others, about the nature of their oppression, they risk subjecting them to further epistemic-moral harms. This is due to the likelihood that at least some of their audience will assign them less/more credibility than they deserve based on pre-existing identity-based prejudices. Second, though some of these requests to ‘educate’ or ‘learn more’ masquerade as seemingly virtuous or innocuous epistemic inquiries, privileged persons underestimate or remain ignorant of secondary harms which stem from internalized epistemic obligations, oppressive double-binds (Hirji, 2021), and attendant emotional burdens oppressed knowers carry in relation to the ever-present possibility of ameliorating oppressor mindsets. After surveying each context-specific harm briefly, we then turn to an applied reading of how these exploitative practices sometimes culminate in something we refer to as ‘ontic burnout’, a form of interminable explanatory fatigue brought on by repeated requests to educate the privileged about what it means to be oppressed. (shrink)

Food security is one of the major concerns in the Philippines. Although livestock and poultry production accounts for a significant proportion of the country’s agricultural output, smallholder households are still vulnerable to food insecurity. The current study aims to examine how livestock production and selling difficulties affect smallholder households’ food-insecure conditions. For this objective, Bayesian Mindsponge Framework (BMF) analytics was employed on a dataset of the Food and Agriculture Organization’s Data in Emergencies Monitoring (DIEM) system. We found that production and (...) selling difficulties significantly adversely affect food insecurity in the Philippines. However, their effects vary according to the severity of food insecurity. In particular, production and selling difficulties affect the households’ likelihood of eating less healthy and nutritious food equally. However, the production difficulties have more negligible impacts on the possibility of skipping meals and even ambiguous impacts on the likelihood of not eating for a whole day compared to the effects of selling difficulties. Moreover, we also found that the market plays a crucial role in facilitating not only livestock trading but also livestock production (e.g., purchase of feed and medicines). Based on these findings, we suggest that the livestock market needs to be expanded and regulated to maintain the balancing prices between livestock products and products and services used for livestock production, and facilitate the product-exchanging mechanism. (shrink)

In order to perform certain actions – such as incarcerating a person or revoking parental rights – the state must establish certain facts to a particular standard of proof. These standards – such as preponderance of evidence and beyond reasonable doubt – are often interpreted as likelihoods or epistemic confidences. Many theorists construe them numerically; beyond reasonable doubt, for example, is often construed as 90 to 95% confidence in the guilt of the defendant. -/- A family of influential cases suggests (...) standards of proof should not be interpreted numerically. These ‘proof paradoxes’ illustrate that purely statistical evidence can warrant high credence in a disputed fact without satisfying the relevant legal standard. In this essay I evaluate three influential attempts to explain why merely statistical evidence cannot satisfy legal standards. (shrink)