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Record W2415541872 · doi:10.7202/1036499ar

Comprendre la prolifération de la renouée du Japon sur les rives du Saint-Laurent

2016· article· fr· W2415541872 on OpenAlexvenueaboutno aff
V. Aubin, Sylvie Bibeau

Bibliographic record

VenueLe Naturaliste canadien · 2016
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesForestryArtGeography

Abstract

fetched live from OpenAlex

Les rives et le fleuve Saint-Laurent sont de plus en plus colonisés par des espèces exotiques envahissantes, dont la renouée du Japon (Fallopia japonica) qui bloque peu à peu les accès à l’eau et bouleverse l’équilibre naturel. Afin de prévenir sa prolifération, le Comité ZIP (Zone d’intervention prioritaire) Jacques-Cartier a étudié sa stratégie de croissance sur le territoire de la Communauté métropolitaine de Montréal. La superficie et la densité des massifs de renouée du Japon ont eu tendance à prendre de l’ampleur entre 2012 et 2013. La croissance de la plante fut plus hâtive sur les rives du fleuve que dans les friches et les boisés voisins. La richesse spécifique d’herbacées a diminué dans les massifs de renouée pendant la saison estivale jusqu’à devenir monospécifique. Une diminution de la richesse d’arthropodes récoltés dans les massifs illustre la modification du réseau trophique que cause cette plante envahissante. Ces impacts menacent l’intégrité écologique des milieux humides des rives du Saint-Laurent.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.395

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.017
GPT teacher head0.204
Teacher spread0.188 · 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
Published2016
Admission routes2
Has abstractyes

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