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Record W4401383854 · doi:10.7202/1112437ar

Funestes volcans ?

2023· article· fr· W4401383854 on OpenAlexvenueno aff
Frédéric Laugrand, Lionel Simon, Pierre Delmelle

Bibliographic record

VenueFrontières · 2023
Typearticle
Languagefr
FieldMedicine
TopicDermatological diseases and infestations
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Intrinsèquement liée à la formation de notre planète et aux mouvements de son écorce superficielle, l’activité volcanique a sans relâche sculpté les milieux physiques. Les volcans et leurs éruptions ont à de nombreuses reprises modifié temporairement le climat de la Terre, métamorphosé les paysages aux échelles régionale et locale, et bouleversé profondément les sociétés, parfois en les rayant irrémédiablement de la carte. D’abord synonymes de destruction et de désolation, les espaces affectés par les coulées de lave ou les épais dépôts de cendres volcaniques, se sont transformés au fil du temps en terres fertiles, offrant de nouvelles opportunités pour les communautés humaines. La fureur mortifère des volcans se confond ainsi, sans paradoxe, avec leur capacité à régénérer la vie (Bobbé, 1998; De Boer et Sanders, 2002; Coutros, 2018). Comme tels, les volcans n’ont eu cesse de nourrir les imaginaires.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.022

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 head0.026
GPT teacher head0.296
Teacher spread0.270 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

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