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Record W4399150742

Lemag' - La revue numérique de la Fondation de l’Université de Guyane Edition n°14 - Juin 2024: - DOSSIER : La Guyane, terre d'immigrationLa dynamique des sociétés amazoniennes dans leurs environnements et la gestion durable des territoires amazoniens- RECHERCHE : Consommation de Manioc et gestion du diabète chez les PalikurLa santé et écologie de la santé en milieu tropical- La dynamique de la biodiversité en Amazonie et valorisation des ressources naturellesENTRETIEN : Les propriétés prometteuses du palmier Moucaya, "Acrocomia Aculeata"- Les technologies innovantes en milieu amazonien et technologies bio-inspirées

2024· other· fr· W4399150742 on OpenAlexaff
Gaëlle Fornet, Suzanne Pons, Julie Ronzon, Sophie Vo, Laurent Linguet, Michael Rapinsky, Damien Davy, Alain Cuerrier, Daniel Giménez, Moustapha Aladji, Marianne Palisse, Wilmont Jean, Abdelhak Qribi, Lily Walter, Wilfried Denagbe

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2024
Typeother
Languagefr
FieldSocial Sciences
TopicMigration, Identity, and Health
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.006
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.137
Threshold uncertainty score0.274

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.002
Scholarly communication0.0070.003
Open science0.0010.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0820.014

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 head0.024
GPT teacher head0.301
Teacher spread0.277 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractno

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