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Record W2401505247

Solving Valid Syllogistic Problems using a Bidirectional Heteroassociative Memory

2014· article· en· W2401505247 on OpenAlexfundno aff
Marie-France Herbert, Sylvain Chartier, Christophe Tremblay

Bibliographic record

VenueeScholarship (California Digital Library) · 2014
Typearticle
Languageen
FieldComputer Science
TopicCognitive Science and Mapping
Canadian institutionsnot available
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsSyllogismDeductive reasoningConnectionismRepresentation (politics)Cognitive scienceComputer scienceSimple (philosophy)Artificial intelligencePsychologyEpistemologyCognitive psychologyArtificial neural networkPhilosophyLaw
DOInot available

Abstract

fetched live from OpenAlex

Classical syllogistic reasoning, also known as Aristotelian reasoning, is of particular interest in cognition.Such reasoning, which can seem simple at first, is known to be associated with high error rates.Although some research has been done on this topic, the underlying mechanisms used by human beings remain largely unknown.To understand the underlying cognitive properties associated with solving syllogistic problems, this study uses a connectionist approach composed of three steps inspired from Laird and Bara (1984): spatial representation, associative memory, and alternative searching conclusion.Results show that the network produces similar performances as humans.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.773
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0030.008
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.033
GPT teacher head0.238
Teacher spread0.205 · 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 designOther design
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

Citations1
Published2014
Admission routes1
Has abstractyes

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