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Record W2964677313 · doi:10.4000/books.psorbonne.26316

Construire sa mémoire

2015· book-chapter· fr· W2964677313 on OpenAlexaff
Marion Chaigne

Bibliographic record

VenueÉditions de la Sorbonne eBooks · 2015
Typebook-chapter
Languagefr
FieldSocial Sciences
TopicDiverse Cultural and Historical Studies
Canadian institutionsBibliothèque et Archives nationales du Québec
Fundersnot available
KeywordsMoiré patternArtComputer scienceComputer vision

Abstract

fetched live from OpenAlex

Les funérailles constituent un moment essentiel de la vie d’un chrétien à la fin du Moyen Âge. Il doit être enterré en bon chrétien, mais aussi racheter ses péchés. Les testaments enregistrés au Parlement de Paris entre 1375 et 1421, dont 31 testaments de femmes, bourgeoises ou nobles, constituent une source exceptionnelle permettant d’étudier l’organisation des funérailles du début du xve siècle. Ces sources permettent de croiser la question de la piété et de la mémoire à celles de la disti...

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)0.002
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 score0.021
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.008
Scholarly communication0.0100.008
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0210.006

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 head0.060
GPT teacher head0.280
Teacher spread0.220 · 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
Published2015
Admission routes1
Has abstractyes

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