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Record W2939102698 · doi:10.7202/1054111ar

La connectivité au-delà des frontières : Résolution 40-3 concernant la connectivité écologique, l’adaptation aux changements climatiques et la conservation de la biodiversité

2018· article· fr· W2939102698 on OpenAlexvenueaboutno aff
Danielle St-Pierre, Antoine Nappi, Sonia de Bellefeuille, Andrée-Anne Lévesque Aubé, Sylvie Martín

Bibliographic record

VenueLe Naturaliste canadien · 2018
Typearticle
Languagefr
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesGeographyPhilosophy

Abstract

fetched live from OpenAlex

En août 2016, la Résolution 40-3 (Résolution concernant la connectivité écologique, l’adaptation aux changements climatiques et la conservation de la biodiversité) a été adoptée lors de la 40e Conférence annuelle des gouverneurs de la Nouvelle-Angleterre et des premiers ministres de l’Est du Canada. Par cette résolution, les gouverneurs et les premiers ministres reconnaissent l’importance de la connectivité écologique pour la capacité d’adaptation et la résilience des écosystèmes, de la biodiversité et des communautés humaines face aux changements climatiques. La résolution souligne également l’importance de collaborer par-delà les frontières afin de faire avancer les efforts de conservation et de rétablissement de la connectivité écologique. Les éléments abordés dans la résolution touchent notamment la conservation, la planification de l’utilisation du territoire, la gestion des ressources naturelles et la planification des infrastructures routières. La mise en oeuvre de cette résolution est assurée par un groupe de travail coprésidé par les gouvernements du Québec et du Vermont. D’ici 2020, les activités du groupe de travail viseront à favoriser la mise en oeuvre d’actions concrètes en matière de connectivité écologique.

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)0.004
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.295
Threshold uncertainty score0.593

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0040.002
Scholarly communication0.0040.001
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.002

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 head0.353
Teacher spread0.297 · 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
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

Citations3
Published2018
Admission routes2
Has abstractyes

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