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Record W2917192627 · doi:10.7202/1055827ar

La documentation historique

2018· article· fr· W2917192627 on OpenAlexvenueno aff
Marla Epp

Bibliographic record

VenueCaptures · 2018
Typearticle
Languagefr
FieldArts and Humanities
TopicCultural Identity and Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsDocumentationComputer scienceProgramming language

Abstract

fetched live from OpenAlex

Nous examinons l’intégration de citations dans Les Onze et HHhH, deux romans à base d’archives avec un narrateur à la première personne qui se veut spécialiste d’histoire. Ce geste citationnel devrait, selon les historiens, produire de la fiabilité, mais n’a pas toujours l’effet escompté. Leur appropriation respective du style historique joue, dans les deux cas, avec les attentes du lecteur et provoque des interrogations quant à la représentation de l’histoire.

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)0.003
metaresearch head score (Gemma)0.008
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: Other · Consensus signal: Other
Teacher disagreement score0.041
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0040.004
Scholarly communication0.0130.005
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0410.009

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 head0.026
GPT teacher head0.262
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 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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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