Firmness, Respiration, and Weight Loss of `Bing', `Lapins' and `Sweetheart' Cherries in Relation to Fruit Maturity and Susceptibility to Surface Pitting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A convenient and reliable method that used a specially designed tool to apply a uniform bruising force in situ was developed to assess the relative susceptibility to fruit surface pitting in sweet cherry. Assessment of pitting with a visual scale after 2 weeks of 1 °C storage was found to be in close agreement with measurements of pit diameter. Using this method `Bing' showed the greatest susceptibility to pitting in both years of the study and `Bing', `Lapins', and `Sweetheart' cherries showed a decline in susceptibility as fruit matured. The predictive value of fruit firmness at harvest, fruit respiration at harvest, and weight loss in storage was assessed in relation to the severity of pitting. The model to best describe pitting was found to include all three physiological variables (firmness, respiration, and weight loss). While an acceptable model was obtained when combining all three cultivars, the best models were achieved when each cultivar was considered separately. It was concluded that there are likely unmeasured variables involved in determining susceptibility to pitting. Hence the best approach to predicting pitting susceptibility is the application of the pit-induction method described in this work.
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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 | 0.000 | 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) | 0.000 | 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 it