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Record W3206217212 · doi:10.4000/books.pup.47878

Attributions multiples, anonymat des textes normatifs : outils et pistes pour une enquête

2016· book-chapter· fr· W3206217212 on OpenAlexaff
Elsa Marguin-Hamon

Bibliographic record

VenuePresses universitaires de Provence eBooks · 2016
Typebook-chapter
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsBibliothèque et Archives nationales du Québec
Fundersnot available
KeywordsPolitical scienceArt

Abstract

fetched live from OpenAlex

L’enquête à mener ici, pas à pas, et comme en temps réel, porte sur deux textes très largement diffusés du xiiie à la fin du xve siècle. Une tradition littéraire déjà ancienne les répertorie sous les titres respectifs de Synonyma et Aequivoca, mais nous délaisserons le second pour lui préférer, ne fiat confusio (un autre texte dont nous serons amenée à parler portant le même), celui d’Homonyma. Il s’agit de deux traités en hexamètres, dont un seul est intégralement édité, l’autre n’ayant été...

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)0.013
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0060.012
Scholarly communication0.0120.022
Open science0.0010.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0070.002

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 head0.040
GPT teacher head0.254
Teacher spread0.214 · 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 designQualitative
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
Published2016
Admission routes1
Has abstractyes

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