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Record W6962637130 · doi:10.1684/agr.2015.0766/pdf

Incidences des changements climatiques sur la compétitivité de quelques cultures du Québec

2015· article· fr· W6962637130 on OpenAlexaboutno aff

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2015
Typearticle
Languagefr
FieldEnvironmental Science
TopicSustainable Agricultural Systems Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPlant productionCrop productionWestern europeProduction system (computer science)Deforestation (computer science)

Abstract

fetched live from OpenAlex

Les changements climatiques provoqueront des modifications des conditions de la production agricole qui devraient se traduire par des impacts sur les rendements et les coûts de production des agriculteurs québécois. Ainsi, la position concurrentielle du Québec pourrait se trouver modifiée par rapport à d’autres régions productrices. À l’aide de la méthode Delphi et de budgets partiels, des scénarios d’impacts des changements climatiques à l’horizon 2050 ont été élaborés et leur impact sur la position concurrentielle du Québec et de ses principales régions concurrentes a été établi pour trois cultures : maïs-grain, pommes, sirop d’érable. Les résultats de l’étude montrent que la position concurrentielle du Québec devrait s’améliorer ou se maintenir pour les productions sous étude grâce à des conditions de production plus favorables au Québec (maïs-grain et pommes) ou à des conditions de production plus défavorables dans les régions compétitrices (sirop d’érable).

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)0.003
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 score0.063
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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