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Record W7126509436

S’emparer de l’inexplicable : le récit mythique et l’appréhension des catastrophes naturelles

2022· article· fr· W7126509436 on OpenAlexaboutno aff
Loredana Lancini, Biophilies antiques ? Manières d’expliquer et d’éprouver les rapports entre humain et nature dans l’Antiquité gréco-romaine

Bibliographic record

VenueDigital Access to Libraries · 2022
Typearticle
Languagefr
FieldArts and Humanities
TopicNarrative Theory and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Identity (music)ElectrocutionNova scotia
DOInot available

Abstract

fetched live from OpenAlex

Dans l'Antiquité, l'avènement des catastrophes naturelles causait des réactions chez les populations qui les vivaient. Ceci est perceptible par exemple dans les tentatives des philosophes de trouver des explications rationnelles. Toutefois, à une lecture approfondie du mythe, on peut comprendre à quel point la narration peut devenir un outil d'appréhension et même de résilience, qui permet la réélaboration de l'expérience traumatique, ainsi que la compréhension des caractéristiques plus exceptionnels de la catastrophe. Cette communication vise à mettre en lumière les caractéristiques qui permettent de reconnaitre cette typologie particulière de récits, les géomythes.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.029
Scholarly communication0.0090.008
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.034
GPT teacher head0.257
Teacher spread0.223 · 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 designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

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