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Record W4394899692 · doi:10.1515/9782763756745-fm

Front Matter

2022· paratext· fr· W4394899692 on OpenAlexaff

Bibliographic record

Venuenot available
Typeparatext
Languagefr
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsFront (military)GeologyOceanography

Abstract

fetched live from OpenAlex

Collection dirigée par Josiane Boulad-Ayoub et Bjarne Melkevik « Le soleil ne transgressera pas son orbe (métra).Ou alors les Érinyes, aides de la justice, le découvriront.» (Héraclite, Aphorisme 94) Les Érinyes, déesses de la vengeance, dont Héraclite fait les auxiliaires de la justice, se métamorphosent à la fin de l'Orestie d'Eschyle en bienveillantes Euménides.Fille de Thémis dans la mythologie, DIKÈ, alliée cependant aux nouvelles divinités Athéna et Apollon, s'humanise dans la tragédie, se laïcise, se politise en s'associant aux progrès de la démocratie, du débat juridique et politique, du développement des lois.DIKÈ n'était pas, à Athènes, la mimésis d'une essence de la justice, elle était à la fois l'idée abstraite du droit et, sous de multiples formes, l'action judiciaire.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.123
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.8770.801

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 head0.020
GPT teacher head0.287
Teacher spread0.267 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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