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Record W2735368507

Quantification And Predication In Modal Predicative Propositional Logic

2015· article· fr· W2735368507 on OpenAlexaff
Daniel Vanderveken

Bibliographic record

VenueLogique et analyse/Logique et analyse. Nouvelle série · 2015
Typearticle
Languagefr
FieldComputer Science
TopicLogic, Reasoning, and Knowledge
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPredicative expressionPropositional variableS5Modal logicIntermediate logicDynamic logic (digital electronics)Propositional calculusTautology (logic)Well-formed formulaIntuitionistic logicPredicate (mathematical logic)Predicate variableComputer scienceLinguisticsModalMathematicsSequentNormal modal logicZeroth-order logicArtificial intelligenceMultimodal logicDescription logicDiscrete mathematicsPhilosophyProgramming language
DOInot available

Abstract

fetched live from OpenAlex

The main objective of this paper is to enrich first order propositional predicative logic by dealing all together with intensional attributes, quantification, logical and historic modalities and ramified time. Predicative propositional logic advocates a finer analysis in terms of predication of the logical form of propositions. Like Church’s logic of sense and denotation (Church 1951), my new predicative approach of quantification is based on Frege’s theory of indirect reference (Frege 1892). However in my approach, like in algebraic intensional logic, generalized propositions predicate first order generalizations of attributes. In the first section, I will analyze in terms of predication the logical form of elementary propositions with all kinds of attributes (whether intensional or extensional) and of generalized, modal and temporal propositions. Next I will define the ideographic object-language of my logic. Its formulas can express different propositions in different contexts of utterance. In the third section, I will define the structure of a standard model for my ideography. In the last section, I will enumerate new valid laws of my logic.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.900
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.319
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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