MétaCan
Menu
Back to cohort
Record W1984842594 · doi:10.7202/002423ar

Tropes et termes : le vocabulaire de la dégustation du vin

2002· article· fr· W1984842594 on OpenAlexvenueno aff
Martine Coutier

Bibliographic record

VenueMeta Journal des traducteurs · 2002
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Depuis les années cinquante, l'engouement pour le vin, boisson à forte charge symbolique, est devenu un phénomène culturel qui s'inscrit dans l'évolution des comportements sociaux et alimentaires. La nouvelle approche du vin implique un nouveau public de dégustateurs, dont le profil se situe entre les spécialistes professionnels (œnologues, experts-dégustateurs), et les simples amateurs. Les impressions gustatives ne correspondant pas à une réalité référentielle objectivable et étant soumises à une forte subjectivité, le vocabulaire qui les décrit est marqué par le recours à l'analogie, la métaphore, caractéristique lexicale renforcée par la composante hédoniste de la dégustation. Cet article se propose d'analyser les tropes lexicaux relevés dans des comptes rendus de dégustation, à travers deux champs thématiques sources de métaphores : le champ du corps humain et celui de la réalité spatiale. La mise en évidence des rapports et des réseaux analogiques et thématiques ainsi que leur ordonnancement permet de dessiner, derrière ce qui peut paraître une imagination lyrique et débridée, un ensemble construit autour de références communes et tendant vers une certaine cohérence.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.006
Scholarly communication0.0060.009
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.028
GPT teacher head0.238
Teacher spread0.210 · 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 designNot applicable
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

Citations24
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueMeta Journal des traducteursSame topicWine Industry and TourismFrench-language works237,207