Improving the Prediction of Processing Bean Maturity Based on the Growing-degree Day Approach
Bibliographic record
Abstract
Four snap bean ( Phaseolus vulgaris L.) cultivars, Goldrush, Teseo, Labrador, and Flevoro, were grown in irrigated fields of southern Quebec between 1985 and 1998. Data on phenology collected from these fields were used to determine which base temperature would best predict time from sowing to maturity. The optimal base temperature was 0 °C for `Goldrush', `Teseo', and `Labrador' and 6.7 °C for `Flevoro'. Adjusting different base temperatures for intermediate developmental stages (emergence, flowering) did not improve the prediction model. All years for a given cultivar were then used to determine the base temperature with the lowest coefficient of variation (CV) for predicting the time from sowing to maturity. A common base temperature of 0 °C was selected for all cultivars, since `Flevoro' was not very sensitive to changes in base temperature. This method improved the prediction of maturity compared with the conventional computation growing-degree days (GDD) with a base of 10 °C. For the years and cultivars used in this study, calculating GDD with a base of 0 °C gave an overall prediction of maturity of 1.7, 1.5, 2.0, and 1.4 days based on average absolute differences, for `Flevoro', `Goldrush', `Teseo', and `Labrador', respectively.
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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 | 0.001 | 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 | 0.001 | 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) | 0.000 | 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".