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Record W4240402942 · doi:10.4000/vertigo.4805

Caroline Toutain, Prévenir les catastrophes écologiques? Les marées noires

2008· article· fr· W4240402942 on OpenAlexvenueno aff
Éric Duchemin

Bibliographic record

VenueVertigO · 2008
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

Les dernières années ont vu se succéder les catastrophes maritimes déclenchant des déversements chimiques importants; Ievooli Sun 4 000 tonnes de styrène; Balu 8 000 tonnes d’acide sulfuriques, Melbridge Bilboa, Lyke Liberator 3 citernes de produits chimiques Bow Eagle 200 tonnes d’Acétate d’éthyle, Prestige 77 000 tonnes de fioul lourd, Erika 10 000 tonnes de Fioul lourd et 20 000 prisonnier de l’épave. Bien que très visibles les marées noires, comme celles provoquées par le Prestige, l’Er...

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.163
Threshold uncertainty score0.324

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0050.004
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 head0.051
GPT teacher head0.256
Teacher spread0.205 · 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
Published2008
Admission routes1
Has abstractyes

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