Evaluation of the risks and profitability for early planting dates and bolt reducing strategies for Quebec celery production
Bibliographic record
Abstract
The risks and profitability associated with four early planting dates, and three different types of bolting risk reduction strategies, were evaluated for Quebec celery production. The four planting dates studied were April 17 th, April 24th, May 1st and May 8 th. The impacts on yield if plants were harvested after eleven week, twelve, thirteen, and fourteen weeks in the field were investigated. The three risk reduction strategies considered were plants grown from planting until June 2nd with no row covers, under floating row covers of spunbonded polyester (Agryl P17, Plastitech) and under floating row covers made of clear, perforated polyethylene (Plastitech). The results suggest that the floating row covers can help plants reach the required market standards sooner that if no row covers were used from the planting date investigated until June 2nd. At the earliest two planting dates, the results suggest that row covers may significantly suppress bolting and allow greater yields at earlier harvest dates. The results also suggest that row covers may provide an advantage at later planting dates, as they may allow for the plants to reach marketable standards sooner. The results also suggest that there is a 50 percent chance of encountering bolting rate of 30 percent or higher if transplanting plants on April 17th. The row covers reduced the probability that plants will bolt to close to zero at for all four planting dates. The most profitable strategy was determined to be planting on April 17th, growing the plants under row covers made of spunbonded polyester (Agryl P17, Plastitech) from planting until June 2nd and then harvesting after the plants had been in the field for thirteen weeks.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".