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Record W2159064755 · doi:10.7202/706002ar

Inventaire des mauvaises herbes dans les pépinières ornementales du Québec

2005· article· fr· W2159064755 on OpenAlexaffvenueabout
David Cloutier, Michèle LeBlanc, Roxanne D. Marcotte

Bibliographic record

VenuePhytoprotection · 2005
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBiology

Abstract

fetched live from OpenAlex

Un inventaire des mauvaises herbes réalisé au cours de l'été 1986 a permis de visiter 53% des superficies en production ornementale au Québec. Les infestations de mauvaises herbes étaient maintenues à de faibles niveaux dans les pépinières visitées grâce aux sarclages manuels et aux hersages mécaniques fréquents. L'inventaire a révélé que les mauvaises herbes vivaces étaient les plus difficiles à réprimer dans les pépinières. Les mauvaises herbes vivaces les plus fréquemment rencontrées étaient la vesce jargeau ( Vicia cracca ), le chiendent ( Agropyron repens ), la prèle des champs ( Equisetum arvense ) et le souchet comestible ( Cyperus esculentus ). Les mauvaises herbes identifiées dans les pépinières étaient, pour la plupart, des espèces communes à d'autres cultures. Toutefois, la rorippe d'Islande ( Rorippa islandica ), la rorippe sylvestre ( Rorippa sylvestris ) et la cardamine de Pennsylvanie ( Cardamine pensylvanica ), mauvaises herbes moins connues, ont démontré un fort potentiel d'envahissement dans les pépinières ornementales.

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 score0.138
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.040
GPT teacher head0.230
Teacher spread0.190 · 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

Citations5
Published2005
Admission routes3
Has abstractyes

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