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
The development of a dynamic diseaseforecasting model to control Entomosporium mespili on Amelanchier alnifolia Q.A. Holtslag, W.R. Remphrey, W.G.D. Fernando, R.G. St-Pierre, and G.H.B. Ash Abstract: Entomosporium leaf and berry spot, which is caused by the fungal pathogen Entomosporium mespili, can cause up to 100 % yield loss in Amelanchier alnifolia (saskatoon) in years when weather conditions are conducive to disease development. In an effort to optimize the effectiveness and minimize the use of fungicides, a dynamic diseaseforecasting model was developed. The model uses a disease pressure index equation, which integrates information regarding the phenological development of saskatoon, the relationship of disease to inoculum potential and production, leaf-wetness duration and temperature, inoculum release, and host susceptibility, to provide an estimate of disease pressure. When the model was evaluated, a strong correlation was found between predicted disease pressure and observed disease symptom development. After the field data were combined, the model could account for 82 % of the variation in the increase of mean lesion number per leaf observed during the preharvest period. Control thresholds, together with application and control guidelines for use of the fungicide propiconazole, were added to the model, which was then evaluated in a field trial. A preliminary field test of the model showed that its use resulted in reduced
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.
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 it