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Record W2803775082 · doi:10.4000/books.pum.4613

L’Astrée et les intermittences de la mémoire

2013· book-chapter· fr· W2803775082 on OpenAlexaff
Julia Chamard-Bergeron

Bibliographic record

VenuePresses de l’Université de Montréal eBooks · 2013
Typebook-chapter
Languagefr
FieldArts and Humanities
TopicHistorical and Literary Analyses
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsMathematics

Abstract

fetched live from OpenAlex

O cruel souvenir de mon bon-heur passé,Sortez de ma mémoire,Helas ! puis que le bien d’une si grande gloire,Est ores effacé ;Effacez vous de mesme, il n’est pas raisonnable,Que vous soyez en moy qui suis si misérable.Honoré d’Urfé, L’Astrée, I, 10 Le roman français, au tournant des années 1660, semble choisir l’amnésie afin de perdre dans un bienfaisant Léthé son passé « romanesque ». C’est à ce moment qu’on cesse d’écrire les romans dits pastoraux, héroïques ou précieux (ceux des d’Urfé, Gom...

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)0.003
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 score0.016
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.013
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.003

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 head0.014
GPT teacher head0.184
Teacher spread0.170 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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