Effects of Preharvest Precipitation, Air Temperature, and Humidity on the Occurrence of Soft Scald in ‘Honeycrisp’ Apples
Bibliographic record
Abstract
The relationship of soft scald incidence (SSI) with precipitation, temperature, and fruit maturity indicators in ‘Honeycrisp’ apples was examined using 7 years of data in Maine and 6 years in Ontario, Canada. Relative humidity was also examined in Maine. Soft scald incidence was highly variable from year to year ranging from 1% to 85% in Maine and from 0% to 76% in Ontario. In Ontario, SSI was negatively related to soluble solids at harvest (partial r 2 = 0.50; P = 0.0041) and negatively related to precipitation during 90 to 120 days from bloom (DFB; partial r 2 = 0.28; P = 0.0344). In Maine, SSI was most strongly related to precipitation in the 90 to 120 DFB (partial r 2 = 0.53; P = 0.0001), maximum air temperature 60 to 90 DFB (partial r 2 = 0.21; P = 0.0001), and number of hours when relative humidity was greater than 85% (partial r 2 = 0.11; P = 0.0001).
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) | 0.000 | 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".