Bibliographic record
Abstract
Sweetpotato ( Ipomea batatas L) was one crop chosen for development in Ontario in response to demand for alternative crops to tobacco and increasing demand for nontraditional vegetables. A wide range of vegetable crops can be grown in the sandy soils on the north shore of lake Erie. In 1999, there were ≈75 acres of sweetpotatoes grown in Ontario. Lack of an early cultivar to fit a short, warm season was a factor limiting production of sweetpotatoes in southern Ontario. Over an 11–growing season period, cultivars of sweetpotato from several breeding programs in the United States were evaluated for suitability to Ontario climatic conditions. Planting to harvest date season totals for heat units, precipitation, vapor pressure deficit (VPD), potential evapotranspiration, and solar radiation were calculated. Yield was regressed on these climatic variables using multiple linear regression. Of the cultivars evaluated, `Beauregard' replaced `Jewel' as the local industry standard after one season's evaluation. Of the numbered lines evaluated, NC9317 appears suitable for commercial trials. Yields varied greatly among years, and the seasonal VPD explained the largest amount of variation in year-to-year yield. Cultivars vary in their response to seasonal VPD. Yield of `Beauregard' increased with increasing seasonal VPD while NC9317 decreased. Cultivars require ability to yield in a short season and the ability to consistently produce under a range of atmospheric VPDs dictated by interannual climatic variation.
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".