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Record W2940009828 · doi:10.7202/1054119ar

Élargissement de l’autoroute 69 : la route sous le premier écopont de l’Ontario

2018· article· fr· W2940009828 on OpenAlexafffundvenueabout
Andrew Healy

Bibliographic record

VenueLe Naturaliste canadien · 2018
Typearticle
Languagefr
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsMinistère des Transports
FundersMinistère des Transports
KeywordsHumanitiesArtGeography

Abstract

fetched live from OpenAlex

La nouvelle autoroute 69 à 4 voies au sud de Sudbury, en Ontario, est un modèle d’intégration de considérations écologiques aux phases de conception et de construction d’une autoroute. La section de 10 km au nord de l’autoroute 637, achevée en 2012, comprend le premier réseau intégré de la province en ce qui concerne les passages fauniques tant pour les grands mammifères que pour les reptiles, ainsi que le premier passage faunique supérieur (écopont) de l’Ontario. Cet article présente le processus de planification entrepris lors du projet, les détails de conception, et les résultats des 5 premières années d’évaluation de l’efficacité des mesures d’atténuation d’impacts sur la grande faune. Le suivi post-construction continue à faire ressortir les succès et les défis des mesures d’atténuation, et il influencera les modifications à apporter dans les contrats de construction au cours des prochaines phases d’élargissement de l’autoroute, de la conception à la construction. L’objectif ultime est de construire 140 km d’autoroute à 4 voies et d’en faire la section autoroutière présentant le plus de mesures d’atténuation d’impacts sur la faune en Ontario, tant pour les grands mammifères que pour les espèces de tortues et de serpents en situation précaire.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.008
GPT teacher head0.222
Teacher spread0.214 · 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

Citations0
Published2018
Admission routes4
Has abstractyes

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