A re-evaluation of crop heat units in the maritime provinces of Canada
Bibliographic record
Abstract
Crop heat units (CHU) are commonly used to rate suitability of corn (Zea mays L.) hybrids and soybean [Glycine max (L.) Merrill] varieties for production in various regions of Canada. The CHU map presently in use for the Maritime provinces is based on climate data from the period 1956 to 1985. This paper presents an updated CHU map for the region using the latest available climate normals (1971 to 2000) and up-to-date interpolation and mapping procedures. Decadal time trends of CHU and water deficits are also examined for seven selected climate stations in the region. Average CHU ratings often increased by 100 units or more for the most recent period, with some exceptions. Station decadal trends from 1955 to 2004 confirmed the warming trend, with an average increase of 86 CHU per decade. Increased CHU have promoted higher potential yields in corn and soybean in the region, although this potential was not likely met during the last decade due to frequent droughts in some areas. However, there is presently little evidence to suggest that higher yield potential will be significantly limited by changing water deficits as a re sult of greenhouse-gas induced global warming in this century. Key words: Corn, Zea mays, soybean, Glycine max, climate trends, yield, water deficits
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".