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Tout simplement noir

2020· article· fr· W3106564638 on OpenAlexaff
Mouloud Mimoun

Bibliographic record

VenueHommes & migrations · 2020
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsWorld Federation of Science Journalists
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Incroyable ! À une période en pleine crise de la Covid-19 qui a vidé les salles de spectacle au point de désespérer les exploitants de salles de cinéma, un film va ramener un public nombreux dans les cinémas : Tout simplement noir. 700 000 entrées en quelques semaines quand des millions de Français sont encore en vacances !Co-réalisé par Jean-Pascal Zadi, humoriste, comédien et cinéaste, et John Wax, photographe, qui a signé surtout des clips, Tout simplement noir est une comédie hilarante s...

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)0.019
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.097
Threshold uncertainty score0.326

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0110.010
Open science0.0010.004
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0970.052

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 head0.051
GPT teacher head0.257
Teacher spread0.207 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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