Phytotoxicity of GF‐120 <sup>®</sup> NF Naturalyte <sup>®</sup> fruit fly bait carrier on sweet cherry ( <i>Prunus avium</i> L.) foliage
Bibliographic record
Abstract
BACKGROUND: Six sweet cherry (Prunus avium L.) cultivars were tested with GF-120 with spinosad (0.2 g L(-1) spinosad bait) or without it (blank bait) to understand leaf phytotoxicity observed in the field. RESULTS: Spinosad bait and blank bait did not differ significantly with respect to damage observed. Leaf damage was found almost exclusively at the abaxial (lower) surfaces with the doses (0, 17, 20, 25 or 40%) and cultivars tested. The effects of the blank bait on abaxial surfaces increased from 24 to 168 h, and with dose, in terms of the proportion of droplets (0.00, 0.42, 0.52, 0.75 or 0.94) and area (0.0, 18.7, 23.5, 40.5 or 91.6 mm) burned. In addition, chlorophyll was reduced with increasing dose on abaxial surfaces (SPAD = 44.6, 36.1, 34.1, 31.0, 21.5), but not on adaxial (upper) surfaces (SPAD = 44.6, 44.2, 44.0, 44.8, 44.4). The chlorophyll level in undamaged leaves (adaxial surfaces) differed by cultivar. Cherry leaves were less damaged by a 20% bait application in June (0.26) than in July (0.46) and August (0.50). Incidental insect leaf feeding at bait locations occurred at a low rate and was highest on abaxial bait surfaces. CONCLUSIONS: Applying GF-120 to the adaxial leaf surface, or at doses of
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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 | 0.000 | 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) | 0.001 | 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".