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Record W7093300471 · doi:10.82204/chn4-q567

La migration assistée d'espèces forestières : perceptions et défis identifiés par le milieu forestier québécois

2025· report· fr· W7093300471 on OpenAlexaffabout

Bibliographic record

VenueMRNF-DEV · 2025
Typereport
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsMinistère des Ressources naturelles et des Forêts (Québec)Université Laval
Fundersnot available
KeywordsContext (archaeology)Face (sociological concept)PerceptionPopulation

Abstract

fetched live from OpenAlex

Que pensent les acteurs et actrices du milieu forestier québécois de la migration assistée d’espèces forestières, une mesure d’adaptation aux changements climatiques? C’est ce que nous avons tenté de découvrir en menant une recherche exploratoire. À l’aide d’une méthodologie utilisée en sciences sociales, nous avons recueilli et analysé leurs perceptions face à cette approche. Nous avons aussi identifié les défis et les occasions qu’elle représente, selon eux, pour le maintien de la résilience des forêts québécoises.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.033
GPT teacher head0.340
Teacher spread0.306 · 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 designQualitative
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
Published2025
Admission routes2
Has abstractyes

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