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Record W6990208248

De nouveaux ravageurs dans les fraisières au Québec, un autre effet des changements climatiques

2022· article· fr· W6990208248 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge UdeS (Institutional Deposit of the University of Sherbrooke) · 2022
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicFood and Agricultural Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsChemical controlCrop productionWestern europe
DOInot available

Abstract

fetched live from OpenAlex

"Le Québec est la principale province productrice de fraises au Canada. En 2018, la production de fraises était évaluée à un volume de plus de 15 millions de tonnes et représentait des revenus de 66 millions de dollars (Gouvernement du Québec, 2021). Malheureusement, dans les années à venir, les rendements de la culture pourraient être perturbés par les effets des changements climatiques. Parmi les nombreuses conséquences des changements climatiques, il pourrait y avoir une augmentation de la pression exercée sur les cultures de fraises par certains ravageurs ou agents pathogènes déjà présents au Québec, mais également une augmentation des introductions de nouveaux insectes ravageurs et de nouvelles maladies (Lehmann et al., 2020). Les changements climatiques ont une influence considérable sur ces insectes, car l’augmentation des températures favorise leur métabolisme et leur développement (Lehmann et al., 2020). Des températures plus élevées perturbent également les autres activités des insectes, comme l’alimentation, la reproduction, la croissance et les déplacements (Weintraub et al., 2019). Par conséquent, les hausses de température auront potentiellement pour effet d’accroître les densités de
\npopulation d’insectes ravageurs dans les champs de fraises et augmenteront l’intensité des dommages ainsi que les pertes de rendements (Figure 1a). [...]"

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.202
Teacher spread0.185 · 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 teacher head, not a consensus.

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
Published2022
Admission routes1
Has abstractyes

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