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Record W1992568855 · doi:10.1080/13554791003620272

The Application of Rules in Morphology, Syntax and Number Processing: A Case of Selective Deficit of Procedural or Executive Mechanisms?

2010· article· en· W1992568855 on OpenAlexaff
Joël Macoir, Marion Fossard, Jean–Luc Nespoulous, Jean‐François Démonet, Anne‐Catherine Bachoud‐Lévi

Bibliographic record

VenueNeurocase · 2010
Typearticle
Languageen
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsProcedural memorySyntaxCognitive psychologyCognitionPsychologyProcedural knowledgeDeclarative memoryComputer scienceCognitive scienceArtificial intelligenceDomain knowledgeNeuroscience

Abstract

fetched live from OpenAlex

Declarative memory is a long-term store for facts, concepts and words. Procedural memory subserves the learning and control of sensorimotor and cognitive skills, including the mental grammar. In this study, we report a single-case study of a mild aphasic patient who showed procedural deficits in the presence of preserved declarative memory abilities. We administered several experiments to explore rule application in morphology, syntax and number processing. Results partly support the differentiation between declarative and procedural memory. Moreover, the patient's performance varied according to the domain in which rules were to be applied, which underlines the need for more fine-grained distinctions in cognition between procedural rules.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.306
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations8
Published2010
Admission routes1
Has abstractyes

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