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Record W3048408731 · doi:10.3917/rma.261.0027

Chius ki le cuer a irascu

2020· article· fr· W3048408731 on OpenAlexaff
Gabriele Giannini

Bibliographic record

VenueLe Moyen Age · 2020
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

La plainte funèbre Chius ki le cuer a irascu , écrite pour l’évêque de Cambrai Enguerrand de Créquy, décédé en 1285, n’est probablement pas un chef-d’œuvre du genre déploratif, mais recèle plusieurs motifs d’intérêt. D’abord, la pièce est l’une des rares déplorations en langue d’oïl consacrées à un haut prélat. Ensuite, elle permet d’observer le rimeur anonyme aux prises avec un défunt dont l’épiscopat fut turbulent et la réputation sulfureuse, donc sa démarche prudente, la place accordée à l’exhortation aux suffrages et les stratégies adoptées pour rendre cet appel recevable et efficace. Enfin, l’examen de la carrière des dignitaires ecclésiastiques interpellés dans la plainte, dont une nouvelle édition est proposée, permet de conclure que celle-ci était destinée au premier cercle du défunt prélat, émanait vraisemblablement du même cénacle et a été composée entre les anciens diocèses de Cambrai et de Thérouanne.

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)0.000
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.127
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.004
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0350.004

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 head0.031
GPT teacher head0.199
Teacher spread0.168 · 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
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

Citations1
Published2020
Admission routes1
Has abstractyes

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