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Record W2265457545 · doi:10.7202/1074398ar

Les échelles de mesure de l’anxiété face à la mort

2021· article· fr· W2265457545 on OpenAlexaffvenue
Lyne St-Amour, Margaret C. Kiely

Bibliographic record

VenueFrontières · 2021
Typearticle
Languagefr
FieldPsychology
TopicDeath Anxiety and Social Exclusion
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesMathematicsArt

Abstract

fetched live from OpenAlex

Les échelles de mesure de l’anxiété face à la mort ont connu un grand essor au cours des dernières années. Leur développement est attribuable au désir de mieux comprendre et connaître le phénomène. Toutefois, les chercheurs sont constamment confrontés à un problème de définition de ce concept qui réfère à une expérience subjective mettant en cause des composantes cognitives et affectives. Jusqu’à maintenant, la majorité des échelles sont construites sans référence explicite à une base théorique. L’application de ces instruments présente un intérêt, principalement dans le domaine de la recherche, et se montre limitée quant à son utilisation clinique.

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)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.023
GPT teacher head0.356
Teacher spread0.333 · 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 designObservational
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

Citations2
Published2021
Admission routes2
Has abstractyes

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