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Record W3155830206 · doi:10.7202/1073759ar

Les médicaments dans le suicide

2020· article· fr· W3155830206 on OpenAlexvenueaboutno aff
Michel Pozo, Brian L. Mishara, Anne Second-Pozo

Bibliographic record

VenueFrontières · 2020
Typearticle
Languagefr
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

L’utilisation des médicaments, et notamment des psychotropes, dans la vie courante a entraîné des changements importants dans la problématique du suicide : pour la première fois, un moyen thérapeutique est utilisé pour se donner la mort et la proportion de tentatives non létales pour chaque décès par suicide a augmenté énormément. Les médicaments constituent le troisième mode de suicide au Canada comme en France, et ils sont impliqués dans plus de 80 % des hospitalisations pour tentatives de suicide dans ces deux pays. Les liens entre médicaments et suicide sont complexes. Une des façons de comprendre le choix d’un médicament comme moyen de suicide est l’association entre les effets escomptés d’un décès par suicide et les effets escomptés de l’utilisation des médicaments qui ont pour objectif de s’en prendre à la tête, contenu de la psyché, et d’attaquer les pensées, les tensions, la souffrance en les endormant.

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 categoriesMeta-epidemiology (narrow), Insufficient 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: none
Teacher disagreement score0.641
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0030.004

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 head0.059
GPT teacher head0.323
Teacher spread0.264 · 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
Published2020
Admission routes2
Has abstractyes

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