Modelled Climate Change Impacts on Spring Canola Production Across British Columbia, Canada
Bibliographic record
Abstract
This paper investigates the impact of projected near future climate trends on the production of spring planted canola (Brassica napus, Brassica rapa, and Brassica juncea of canola classification) across British Columbia, Canada. Analysis of historic climate trends from 2001-2020, informed by the Global Historical Climatology Network daily (GHCNd) database, establishes patterns of warming temperatures and increasing precipitation values across the province over the early 21st century. Near future climate trends were modelled using CMIP6 climate models, from 2021-2040 under SSP1-2.6, SSP2-4.5 and SSP5-8.5, with the projections downscaled using ClimateBC. The projected trends mirrored those of the observed historic record, while an observable relationship between rising levels of climate change and increasing projected annual precipitation and temperature is recorded. The subsequent crop modelling using the CSM-CROPGRO-Canola and DNDC models, fed with the modelled climate trends, highlighted the expectation for near future climate change to cause significant decreases in spring canola production across British Columbia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".