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Record W1983535588 · doi:10.3917/th.644.0321

Profil statistique des affections vertébrales avec indemnités dans l'industrie de la construction au Québec

2001· article· fr· W1983535588 on OpenAlex
Patrice Duguay, Esther Cloutier, M. Lévy, Pier-Luc Massicotte

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLe travail humain · 2001
Typearticle
Languagefr
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travail
Fundersnot available
KeywordsGynecologyMedicine

Abstract

fetched live from OpenAlex

<titre>R&#201;SUM&#201;</titre> Au Qu&#233;bec, en&#160;1995, 1 400 des 6 400&#160;l&#233;sions professionnelles survenues dans l&#8217;industrie de la construction sont des affections vert&#233;brales. Les man&#339;uvres constituent la profession dont le niveau d&#8217;incidence des affections vert&#233;brales est le plus &#233;lev&#233;&#160;; suivis par la cat&#233;gorie des &#8220; autres m&#233;tiers et occupations &#8221; (ferrailleur, soudeur, homme de service,&#160;etc.) ainsi que par les ferblantiers. Sept sc&#233;narios d&#8217;accidents sont ressortis des analyses multivari&#233;es. Les variables les plus statistiquement significatives pour diff&#233;rencier les sc&#233;narios sont, par ordre d&#8217;importance, le geste ex&#233;cut&#233;, le genre d&#8217;accident, l&#8217;agent causal de la blessure, la t&#226;che effectu&#233;e et la profession. Les affections vert&#233;brales sont plus souvent qu&#8217;attendu associ&#233;es &#224; l&#8217;ex&#233;cution de t&#226;ches connexes aux t&#226;ches qualifi&#233;es (manutention, t&#226;che pr&#233;paratoire ou subs&#233;quente &#224; une t&#226;che sp&#233;cialis&#233;e, d&#233;placement). Ces r&#233;sultats font ressortir l&#8217;importance d&#8217;orienter la pr&#233;vention et la recherche sur ce type de t&#226;ches effectu&#233;es par des man&#339;uvres mais aussi d&#8217;autres professions (charpentier-menuisier, travailleur de la finition int&#233;rieure,&#160;etc.).

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.056
GPT teacher head0.414
Teacher spread0.358 · 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