Most quantifiers have many meanings.

In this paper, we investigate, by means of a computational model, how individuals map quantifiers onto numbers and how they order quantifiers on a mental line. We selected five English quantifiers (few, fewer than half, many, more than half, and most) which differ in truth conditions and vagueness. We collected binary truth value judgment data in an online quantifier verification experiment. Using a Bayesian three-parameter logistic regression model, we separated three sources of individual differences: truth condition, vagueness, and response error. Clustering on one of the model's parameter that corresponds to truth conditions revealed four subgroups of participants with different quantifier-to-number mappings and different ranges of the mental line of quantifiers. Our findings suggest multiple sources of individual differences in semantic representations of quantifiers and support a conceptual distinction between different types of imprecision in quantifier meanings. We discuss the consequence of our findings for the main theoretical approaches to quantifiers: the bivalent truth-conditional approach and the fuzzy logic approach. We argue that the former approach neither can explain inter-individual differences nor intra-individual differences in truth conditions of vague quantifiers. The latter approach requires further specification to fully account for individual differences demonstrated in this study.

Vagueness as an implicit-encoding persuasive strategy: an experimental approach.

The paper provides novel theoretical and experimental perspectives on the functioning of linguistic vagueness as an implicit persuasive strategy. It presents an operative definition of pragmatically marked vagueness, referring to vague expressions whose interpretation is not retrievable by recipients. The phenomenon is illustrated via numerous examples of its use in predominantly persuasive texts (i.e., advertising and political propaganda) in different languages. The psycholinguistic functioning of vague expressions is then illustrated by the results of a self-paced reading task experiment. Data showing shorter reading times associated with markedly vague expressions as compared to expressions that are either (a) lexically more precise or (b) made precise by the context suggest that the former are interpreted in a shallow way, without searching for and/or retrieving exact referents. These results support the validity of a differentiation between context-supported vs. non-supported vague expressions. Furthermore, validation of using marked vagueness as a persuasive implicit strategy which reduces epistemic vigilance is provided.

Semantic Adaptation to the Interpretation of Gradable Adjectives via Active Linguistic Interaction.

When communicating, people adapt their linguistic representations to those of their interlocutors. Previous studies have shown that this also occurs at the semantic level for vague and context-dependent terms such as quantifiers and uncertainty expressions. However, work to date has mostly focused on passive exposure to a given speaker's interpretation, without considering the possible role of active linguistic interaction. In this study, we focus on gradable adjectives big and small and develop a novel experimental paradigm that allows participants to ask clarification questions to figure out their interlocutor's interpretation. We find that, when in doubt, speakers do resort to this strategy, despite its inherent cognitive cost, and that doing so results in higher semantic alignment measured in terms of communicative success. While not all question-answer pairs are equally informative, we show that speakers become better questioners as the interaction progresses. Yet, the higher semantic alignment observed when speakers are able to ask questions does not increase over time. This suggests that conversational interaction's key advantage may be to boost coordination without committing to long-term semantic updates. Our findings shed new light on the mechanisms used by speakers to achieve semantic alignment and on how language is shaped by communication.

Multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers.

Multicriteria Decision Making (MCDM) has a huge role to play while ruling out one suitable alternative among a pool of alternatives governed by predefined multiple criteria. Some of the factors like imprecision, lack of information/data, etc., which are present in traditional MCDM processes have showcased their lack of efficiency and hence eventually it has paved the ways for the development of Fuzzy multicriteria decision making (FMCDM). In FMCDM processes, the decision makers can model most of the real-life phenomena by fuzzy information-based preferences. The availability of a wide literature on similarity measure (SM) emphasizes the vital role of SM of generalized fuzzy numbers (GFNs) to conduct accurate and precise decision making in FMCDM problems. Despite having few advantages, most of the existing approaches possessed a certain degree of counter intuitiveness and discrepancies. Thus, we have attempted to propose a novel SM for generalized trapezoidal fuzzy numbers (GTrFNs) which could deliberately overcome the impediments associated with the earlier existing approaches. Moreover, a meticulous comparative study with the existing approaches is also presented. This paper provides us with an improved method to obtain the similarity values between GTrFNs and the proposed SM consists of calculating the prominent features of fuzzy numbers such as expected value and variance. We use fourteen different sets of GTrFNs, to compare the fruition of the present approach with the existing SM approaches. Furthermore, to show the utility and applicability of our proposed measure, we illustrate few practical scenarios such as the launching of an electronic gadget by a company, a problem of medical diagnosis and finally, a proper anti-virus mask selection in light of the recent COVID-19 pandemic. The obtained results with our proposed SM, for the mentioned FMCDM problems, are analytically correct and they depict the efficiency and novelty of the present article.

Prioritizing severity level of COVID-19 using correlation coefficient and intuitionistic fuzzy logic.

During the peak of COVID-19 pandemic crisis in 2020 and 2021, with limited medical resources and surge in Covid cases in every hospital and clinic, identifying the most vulnerable patient requiring immediate critical treatment was a great challenge for the medical practitioners. And if such a patient suffers from multiple ailments, his/her condition may deteriorate rapidly if proper treatment is delayed any further. In this paper, we used a novel method which supports medical care units in identifying the patients who need urgent medical treatment. We used Gerstenkorn and Manko correlation coefficient and the intuitionistic fuzzy sets to classify such patients, who should be given the highest priority to start the treatment first. The role of this correlation measurement is very vital in any decision-making process. An intuitionistic fuzzy set (IFS) handles uncertainty, vagueness, ambiguity etc. present in the data and helps in making decision process more realistic. Combining the correlation coefficient with the Intuitionistic fuzzy set makes the decision making process more easy, accurate and reliable. We used COVID-19 dataset which maintains early-stage symptoms of COVID-19 patients, and is publicly available. We applied correlation coefficient and IFS to predict the severity level of the COVID-19 cases by establishing the relationship between the patient and the ailments a COVID-19 patient is suffering from.

Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions.

INTRODUCTION: Currently, one of the commonly used methods for disseminating electronic health record (EHR)-based phenotype algorithms is providing a narrative description of the algorithm logic, often accompanied by flowcharts. A challenge with this mode of dissemination is the potential for under-specification in the algorithm definition, which leads to ambiguity and vagueness. METHODS: This study examines incidents of under-specification that occurred during the implementation of 34 narrative phenotyping algorithms in the electronic Medical Record and Genomics (eMERGE) network. We reviewed the online communication history between algorithm developers and implementers within the Phenotype Knowledge Base (PheKB) platform, where questions could be raised and answered regarding the intended implementation of a phenotype algorithm. RESULTS: We developed a taxonomy of under-specification categories via an iterative review process between two groups of annotators. Under-specifications that lead to ambiguity and vagueness were consistently found across narrative phenotype algorithms developed by all involved eMERGE sites. DISCUSSION AND CONCLUSION: Our findings highlight that under-specification is an impediment to the accuracy and efficiency of the implementation of current narrative phenotyping algorithms, and we propose approaches for mitigating these issues and improved methods for disseminating EHR phenotyping algorithms.

Can the Future-Like-Ours Argument Survive Ontological Scrutiny?

We argue that the future-like-ours argument against abortion rests on an important assumption. Namely, in the first trimester of an aborted pregnancy, there exists something that would have gone on to enjoy conscious mental states, had the abortion not occurred. To accommodate this assumption, we argue, a proponent of the future-like-ours argument must presuppose that there is ontic vagueness. We anticipate the objection that our argument achieves "too much" because it also applies mutatis mutandis to conscious humans. We respond by showing that an explanation can be given for why it is wrong to kill conscious humans that is independent of the underlying metaphysics. Our response brings into focus a reason why-at least in the context of an ethical argument like the future-like-ours argument-appeal to a highly controversial metaphysics is ad hoc. Such metaphysics is not necessary to explain the wrongness of killing conscious humans, only nonconscious fetuses.

Capturing richer information: On establishing the validity of an interval-valued survey response mode.

Obtaining quantitative survey responses that are both accurate and informative is crucial to a wide range of fields. Traditional and ubiquitous response formats such as Likert and visual analogue scales require condensation of responses into discrete or point values-but sometimes a range of options may better represent the correct answer. In this paper, we propose an efficient interval-valued response mode, whereby responses are made by marking an ellipse along a continuous scale. We discuss its potential to capture and quantify valuable information that would be lost using conventional approaches, while preserving a high degree of response efficiency. The information captured by the response interval may represent a possible response range-i.e., a conjunctive set, such as the real numbers between 3 and 6. Alternatively, it may reflect uncertainty in respect to a distinct response-i.e., a disjunctive set, such as a confidence interval. We then report a validation study, utilizing our recently introduced open-source software (DECSYS), to explore how interval-valued survey responses reflect experimental manipulations of several factors hypothesised to influence interval width, across multiple contexts. Results consistently indicate that respondents used interval widths effectively, and subjective participant feedback was also positive. We present this as initial empirical evidence for the efficacy and value of interval-valued response capture. Interestingly, our results also provide insight into respondents' reasoning about the different aforementioned types of intervals-we replicate a tendency towards overconfidence for those representing epistemic uncertainty (i.e., disjunctive sets), but find intervals representing inherent range (i.e., conjunctive sets) to be well-calibrated.

Is it Reasonable to Study Decision-Making Quantitatively?

Scientists studying decision-making often provide a set of choices, each specified with values or distributions of values, and probabilities or distributions of probabilities. For example, "Would you prefer $100 with probability 1.0 or $1 with probability .9 and $1,000 with probability 0.1?" Other decision research examines choices made in the absence of most quantitative information; for example, "Would you prefer a Ford now or a Porsche a year from now?," "Which food would you prefer," but models the findings with precise quantitative assumptions. Yet other research does neither; for example, modeling verbally stated choices with verbally stated heuristics. This article asks about the relevance of the first two research approaches for much of the decision-making made in life. The use of quantitative research and modeling is unsurprising, given that this approach underlies most of science. In life, values and probabilities are almost always partly or wholly vague and qualitative rather than quantitative. For example, when deciding which house to buy, there are relevant features such as size, color, neighborhood schools, construction materials, attractiveness, and many more, but the decision-maker finds it difficult and of little use to assign these precise values or weights. Nonetheless, humans have evolved to make decisions in such vaguely specified settings. I provide an example showing how a very high degree of uncertainty can defeat the application of quantitative decision-making, but such a demonstration is not critical if quantitative research and modeling produce a good understanding of and a good approximation to decision-making in the natural environment. This perspective addresses these issues.

Slipping on slippery slope arguments.

Slippery slope arguments (SSAs) are used in a wide range of philosophical debates, but are often dismissed as empirically ill-founded and logically fallacious. In particular, leading authors put forward a meta-SSA which points to instances of empirically ill-founded and logically fallacious SSAs and to the alleged existence of a slippery slope leading to such SSAs to demonstrate that people should avoid using SSAs altogether. In this paper, I examine these prominent calls against using SSAs and argue that such calls do not withstand scrutiny. I then identify several types of mechanisms leading to slippery slopes in real-life contexts to demonstrate that both the strength of SSAs and the justifiability of using SSAs are best assessed on a case-by-case basis. This result does not exempt the proponents of SSAs from the task of vindicating their use of SSAs. However, if correct, it undermines the often-made claim that people should avoid using SSAs altogether.

Places as fuzzy locational categories.

This paper offers a new way of considering places as special types of categories, in human cognition of larger-scale environments. This may provide an explanatory cognitive model for a range of known phenomena from environmental psychology and human geography - notably places' semantic salience and vague, unstable boundaries. Using such a model to apply suitable classification approaches may enhance geographic information (GI) for key public-facing users, such as emergency services and planners. Two empirical studies confirmed that a spatially extended place (e.g., suburban locality or neighborhood) may be stored as a category whose exemplars are memorable individual locations or scenes. Using a questionnaire-based method to partly replicate key findings from the semantic memory literature (Barsalou, 1985; Lynch et al., 2000), the studies tested the relevance to such places of known semantic memory phenomena including graded membership, typicality versus ideals, expertise and context effects. The discussion considers the link between semantic and spatial vagueness of places.

Revealing Criterial Vagueness in Inconsistencies.

Sixty undergraduate students made category membership decisions for each of 132 candidate exemplar-category name pairs (e.g., chess - Sports) in each of two separate sessions. They were frequently inconsistent from one session to the next, both for nominal categories such as Sports and Fish, and ad hoc categories such as Things You Rescue from a Burning House. A mixture model analysis revealed that several of these inconsistencies could be attributed to criterial vagueness: participants adopting different criteria for membership in the two sessions. This finding indicates that categorization is a probabilistic process, whereby the conditions for applying a category label are not invariant. Individuals have various functional meanings of nominal categories at their disposal and entertain competing goals for ad hoc categories.

The quantitative measuring method of meibomian gland vagueness and diagnostic efficacy of meibomian gland index combination.

PURPOSE: To propose and to evaluate a quantitative measuring method of meibomian gland (MG) vagueness. METHODS: A total of 47 patients (32 female and 15 male, 39.21 ± 11.07 years) with meibomian gland dysfunction (MGD) were recruited to the MGD group, and 47 healthy volunteers were recruited to the control group matched in age and gender. The clinical examinations included ocular surface evaluation, MG function indexes and MG morphological indexes (including MG vagueness value). Reliability and efficacy of MG vagueness value, correlation between vagueness value and relevant variables, and diagnostic efficacy of combining vagueness value with efficacious indexes were all evaluated. RESULTS: The MG vagueness value of the MGD group (19.78 ± 13.17) was significantly lower than that of the control group (31.90 ± 13.15). The vagueness value possessed good between-reader reliability (intraclass correlation coefficient = 0.928 > 0.9), and was correlated with age (r = -0.356), most clinical indexes and the acinar shortest diameter (r = -0.278). The area under the curve (AUC) in the receiver operating characteristic (ROC) curve of vagueness value was 0.766 [95% confidence interval (CI): 0.668-0.864] with sufficient diagnostic efficacy, and the cutoff value was <21. The AUC improved to 0.956 (95% CI: 0.938-0.999), after efficacious indexes (vagueness value, meiboscore and tear breakup time) were combined. CONCLUSION: Meibomian gland (MG) vagueness is quantifiable. The MG vagueness value proposed in this study has good reliability, a close relationship with MGD clinical features and sufficient diagnostic efficacy. Combining this new index with other indexes commonly used offers an exciting prospect in MGD diagnosis.

Cognitive Metaphysics.

In recent years philosophers have been interested in the methodology of metaphysics. Most of these developments are related to formal work in logic or physics, often against the backdrop of the Carnap-Quine debate on ontology. Drawing on Quine's later work, I argue that a psychological or cognitive perspective on metaphysical topics may be a valuable addition to contemporary metametaphysics. The method is illustrated by means of cognitive studies of the notions "identity," "vagueness," and "object" and is compared to other extant metametaphysical positions.

Aplicación de un árbol de decisión difusa con clasificación de ambigüedad para determinar el exceso de peso en escolares / Application of a fuzzy decision tree with ambiguity classification to determine excess weight in schoolchildren

RESUMEN La técnica del árbol de decisiones en las ciencias de la salud sirve para comprender las correlaciones entre las descripciones de los pacientes y para clasificar de forma precisa en diversas categorías. El objetivo del estudio fue analizar la exactitud de la clasificación del exceso de peso de escolares mediante la aplicación de un árbol de decisión difusa, utilizando una base de datos de Itaupú, Paraná (Brasil). Se utilizó la base de datos de una muestra conformada por 5962 estudiantes (3024 del sexo femenino y 2938 del sexo masculino), con un rango de edad entre los 6 a 17 años de edad. Las variables consideradas fueron peso, estatura y el Índice de Masa Corporal (IMC). Para clasificar los datos antropométricos de los escolares se utilizó un árbol de decisión difusa. Los resultados del aprendizaje mostraron una clasificación correcta en el sexo femenino de 2688 y en el sexo masculino de 2471 registros respectivamente. En relación a la exactitud, se determinó 84% en el sexo masculino y 89% en el sexo femenino. El Área Bajo la curva mostró valores más altos en el método Difuso y en ambos sexos (0.965-0.983), mientras que en el método clásico, fueron inferiores (0.804-0.895). De acuerdo a los resultados calculados es posible aplicar el árbol de decisión difusa para la clasificación de escolares con exceso de peso con una exactitud aceptable, además se presenta como una técnica alternativa que puede ahorrar tiempo a la hora de analizar el estado nutricional, sin embargo, no se realizó otros cálculos estadísticos que tengan que ver con la precisión y exactitud a través de métodos estadísticos convencionales y comparar con la técnica de árboles difusos.

ABSTRACT The decision tree technique in the health sciences serves to understand the correlations between the descriptions of patients and to classify accurately in various categories. The aim of the study was to analyze the accuracy of the classification of excess weight of schoolchildren through the application of a fuzzy decision tree, using a database of Itaupú, Paraná (Brazil). We used the database of a sample consisting of 5962 students (3024 female and 2938 male), with an age range between 6 to 17 years of age. The variables considered were weight, height and the Body Mass Index (BMI). To classify the anthropometric data of the students, a diffuse decision tree was used. The learning results showed a correct classification in the female sex of 2688 and in the male sex of 2471 records respectively. In relation to accuracy, 84% was determined in the male sex and 89% in the female sex. The Area under the curve showed higher values in the Fuzzy method and in both sexes (0.965-0.983), while in the classical method, they were lower (0.804-0.895). According to the calculated results it is possible to apply the fuzzy decision tree for the classification of overweight students with an acceptable accuracy, and it is presented as an alternative technique that can save time when analyzing the nutritional status, however, no other statistical calculations were made that have to do with the precision and accuracy through conventional statistical methods and compare with the technique of fuzzy trees.

The Role of Type and Source of Uncertainty on the Processing of Climate Models Projections.

Scientists agree that the climate is changing due to human activities, but there is less agreement about the specific consequences and their timeline. Disagreement among climate projections is attributable to the complexity of climate models that differ in their structure, parameters, initial conditions, etc. We examine how different sources of uncertainty affect people's interpretation of, and reaction to, information about climate change by presenting participants forecasts from multiple experts. Participants viewed three types of sets of sea-level rise projections: (1) precise, but conflicting; (2) imprecise, but agreeing, and (3) hybrid that were both conflicting and imprecise. They estimated the most likely sea-level rise, provided a range of possible values and rated the sets on several features - ambiguity, credibility, completeness, etc. In Study 1, everyone saw the same hybrid set. We found that participants were sensitive to uncertainty between sources, but not to uncertainty about which model was used. The impacts of conflict and imprecision were combined for estimation tasks and compromised for feature ratings. Estimates were closer to the experts' original projections, and sets were rated more favorably under imprecision. Estimates were least consistent with (narrower than) the experts in the hybrid condition, but participants rated the conflicting set least favorably. In Study 2, we investigated the hybrid case in more detail by creating several distinct interval sets that combine conflict and imprecision. Two factors drive perceptual differences: overlap - the structure of the forecast set (whether intersecting, nested, tangent, or disjoint) - and asymmetry - the balance of the set. Estimates were primarily driven by asymmetry, and preferences were primarily driven by overlap. Asymmetric sets were least consistent with the experts: estimated ranges were narrower, and estimates of the most likely value were shifted further below the set mean. Intersecting and nested sets were rated similarly to imprecision, and ratings of disjoint and tangent sets were rated like conflict. Our goal was to determine which underlying factors of information sets drive perceptions of uncertainty in consistent, predictable ways. The two studies lead us to conclude that perceptions of agreement require intersection and balance, and overly precise forecasts lead to greater perceptions of disagreement and a greater likelihood of the public discrediting and misinterpreting information.

Applying systems biology to biomedical research and health care: a précising definition of systems medicine.

BACKGROUND: Systems medicine has become a key word in biomedical research. Although it is often referred to as P4-(predictive, preventive, personalized and participatory)-medicine, it still lacks a clear definition and is open to interpretation. This conceptual lack of clarity complicates the scientific and public discourse on chances, risks and limits of Systems Medicine and may lead to unfounded hopes. Against this background, our goal was to develop a sufficiently precise and widely acceptable definition of Systems Medicine. METHODS: In a first step, PubMed was searched using the keyword "systems medicine". A data extraction tabloid was developed putting forward a means/ends-division. Full-texts of articles containing Systems Medicine in title or abstract were screened for definitions. Definitions were extracted; their semantic elements were assigned as either means or ends. To reduce complexity of the resulting list, summary categories were developed inductively. In a second step, we applied six criteria for adequate definitions (necessity, non-circularity, non-redundancy, consistency, non-vagueness, and coherence) to these categories to derive a so-called précising definition of Systems Medicine. RESULTS: We identified 185 articles containing the term Systems Medicine in title or abstract. 67 contained at least one definition of Systems Medicine. In 98 definitions, we found 114 means and 132 ends. From these we derived the précising definition: Systems Medicine is an approach seeking to improve medical research (i.e. the understanding of complex processes occurring in diseases, pathologies and health states as well as innovative approaches to drug discovery) and health care (i.e. prevention, prediction, diagnosis and treatment) through stratification by means of Systems Biology (i.e. data integration, modeling, experimentation and bioinformatics). Our study also revealed the visionary character of Systems Medicine. CONCLUSIONS: Our insights, on the one hand, allow for a realistic identification of actual ethical as well as legal issues arising in the context of Systems Medicine and, in consequence, for a realistic debate of questions concerning its matter and (future) handling. On the other hand, they help avoiding unfounded hopes and unrealistic expectations. This especially holds for goals like improving patient participation which are intensely debated in the context of Systems Medicine, however not implied in the concept.

The Line-drawing Problem in Disease Definition.

Biological dysfunction is regarded, in many accounts, as necessary and perhaps sufficient for disease. But although disease is conceptualized as all-or-nothing, biological functions often differ by degree. A tension is created by attempting to use a continuous variable as the basis for a categorical definition, raising questions about how we are to pinpoint the boundary between health and disease. This is the line-drawing problem. In this paper, we show how the line-drawing problem arises within "dysfunction-requiring" accounts of disease, such as those of Christopher Boorse and Jerome Wakefield. We then provide several detailed examples to establish that biological dysfunction cannot provide a boundary. We examine potential ways of resolving the line-drawing problem, either by dropping one of the claims that generates it, or by appealing to additional criteria. We argue that two of these options are plausible, and that each of these can be applied with regard to different diseases.

Blurring nature at its boundaries. Vague phenomena in current stem cell debate.

This paper illuminates the explanatory role of vagueness und species membership against the background of scientific developments in recent stem cell research. With the help of the Neo-Aristotelian concept of "life form naturalism" ontologically vague entities such as stem cells, all above induced pluripotent stem cells (iPS), could be described as necessary constituents for the correct sorting and naming of natural processes and its bearers. Furthermore this specific assessment allows drawing some important ontological and ethical consequences.

Interindividual variability in auditory scene analysis revealed by confidence judgements.

Because musicians are trained to discern sounds within complex acoustic scenes, such as an orchestra playing, it has been hypothesized that musicianship improves general auditory scene analysis abilities. Here, we compared musicians and non-musicians in a behavioural paradigm using ambiguous stimuli, combining performance, reaction times and confidence measures. We used 'Shepard tones', for which listeners may report either an upward or a downward pitch shift for the same ambiguous tone pair. Musicians and non-musicians performed similarly on the pitch-shift direction task. In particular, both groups were at chance for the ambiguous case. However, groups differed in their reaction times and judgements of confidence. Musicians responded to the ambiguous case with long reaction times and low confidence, whereas non-musicians responded with fast reaction times and maximal confidence. In a subsequent experiment, non-musicians displayed reduced confidence for the ambiguous case when pure-tone components of the Shepard complex were made easier to discern. The results suggest an effect of musical training on scene analysis: we speculate that musicians were more likely to discern components within complex auditory scenes, perhaps because of enhanced attentional resolution, and thus discovered the ambiguity. For untrained listeners, stimulus ambiguity was not available to perceptual awareness.This article is part of the themed issue 'Auditory and visual scene analysis'.