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Record W2025313082 · doi:10.3166/ria.17.869-881

Métaphore verbale et approximation

2003· article· fr· W2025313082 on OpenAlexvenueno aff
Karine Duvignau

Bibliographic record

VenueRevue d intelligence artificielle · 2003
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPhilosophyHumanities

Abstract

fetched live from OpenAlex

Notre etude associe une approche linguistique et psycholinguistique du phenomene « metaphore » basee sur des enonces spontanes d'enfants de 2-4 ans ainsi que sur des productions d'adultes dans des textes scientifiques pour large public. Nous voudrions montrer en quel sens ces enonces, generalement consideres soit comme « deviants » soit comme « ordinaires », peuvent apporter un eclairage a la fois de la structuration du lexique des verbes chez le jeune enfant et l'organisation du lexique des verbes chez l'adulte. Concernant les enonces produits par les jeunes enfants, nous developpons des arguments qui vont a l'encontre des notions d'« erreur » ou de « metaphore » qui sont quasi systematiquement investies.

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)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.006
Scholarly communication0.0060.006
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.063
GPT teacher head0.298
Teacher spread0.235 · 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 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

Citations20
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueRevue d intelligence artificielleSame topicLinguistics and Discourse AnalysisFrench-language works237,207