Impact of high air temperatures on Brassicacae crops in southern Ontario
Bibliographic record
Abstract
The yield patterns of many cool season vegetable crops were observed to be different from the gradual increase in yields that has been reported over time for corn and soybeans in Ontario. A study was conducted to determine if there was a relationship between yield and seasonal weather patterns for five vegetables (broccoli, cabbage, cauliflower, radish and rutabaga) in the family Brassicacae. The iterative chi-squared technique was used to identify correlations between daily temperature and marketable yield. Yields of all five of the crops showed some damage due to hot weather in August. For cauliflower, cabbage and rutabaga there was roughly a 10% yield loss for every 10 d that the temperature reached 30°C or above during the growing season. These results shed new insight into the mechanisms by which weather affects yield. Key words: Cabbage, broccoli, cauliflower, radish, rutabaga, yield, climate
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".