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Typologie des bandes dessinées numériques

2016· book-chapter· fr· W2982437109 on OpenAlexaff
Magali Boudissa

Bibliographic record

VenueCNRS Éditions eBooks · 2016
Typebook-chapter
Languagefr
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsCentre Intégré de Santé et de Services Sociaux des Laurentides
Fundersnot available
KeywordsGeologyComputer science

Abstract

fetched live from OpenAlex

Ce que l’on nomme aujourd’hui « bande dessinée numérique » ou webcomic en anglais, recouvre un large champ d’œuvres incluant des bandes dessinées papier numérisées ainsi que des récits interactifs et multimédia. Si les relations entre le 9e art et le numérique se nouent de manière multiple, cet article propose une typologie des récits consultables sur écran numérique (smartphone, tablette ou ordinateur). Pour ce faire, nous observerons les différentes configurations techniques des webcomics a...

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: Qualitative · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0030.007
Scholarly communication0.0060.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.003

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 head0.067
GPT teacher head0.254
Teacher spread0.187 · 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 designQualitative
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

Citations45
Published2016
Admission routes1
Has abstractyes

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