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Record W2587425847 · doi:10.4000/pistes.4953

Souffrance au travail et enjeux de santé : le rôle charnière de l’inflammation et du stress oxydant

2017· article· fr· W2587425847 on OpenAlexvenueno aff
Philippe Davezies

Bibliographic record

VenuePerspectives interdisciplinaires sur le travail et la santé · 2017
Typearticle
Languagefr
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPsychologyPhilosophy

Abstract

fetched live from OpenAlex

Une maladie professionnelle engage la responsabilité de l’employeur. Elle ouvre sur un contentieux dans lequel l’arbitrage scientifique est attendu essentiellement de l’épidémiologie. Cet enjeu pèse sur la compréhension des liens entre santé et travail, car il focalise l’attention sur les relations causales simples et tend à laisser dans l’ombre les effets liés au contexte et à l’histoire. Nous présentons pourtant le cas d’une salariée qui illustre l’importance de ces dimensions. À la suite d’une exposition prolongée à un stress psychosocial et à de fortes contraintes gestuelles et posturales, elle a été traitée pour une hypertension artérielle, pour une dépression et pour une longue série de troubles musculo-squelettiques. Ce cas permet d’attirer l’attention sur le rôle central de l’inflammation et du stress oxydant, non seulement en matière de liens entre souffrance psychique et atteintes du corps mais, au-delà, pour la compréhension des interactions entre les différentes contraintes et nuisances du travail, agressions toxiques comprises.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.018
GPT teacher head0.345
Teacher spread0.327 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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