Impact of <i>n</i>C24 agricultural mineral oil deposits on the searching efficiency and predation rate of the predatory mite <i>Phytoseiulus persimilis</i> Athias‐Henriot (Acari: Phytoseiidae)
Bibliographic record
Abstract
Abstract Walking activity, walking straightness, walking speed and searching efficiency of the predatory mite Phytoseiulus persimilis Athias‐Henriot were measured on French bean leaf discs that were sprayed with either distilled water, or one of 0.25%, 0.50% and 1.00% w/w aqueous emulsions of an n C24 agricultural mineral oil (AMO). There was no significant difference in percentage of time that mites spent walking in the control (water‐sprayed) conditions and in any of the oil treatments. Walking paths were significantly straighter in the oil treatments than in the control, but differences among the oil treatments did not differ significantly. Walking speeds in the oil treatments were significantly slower than in the control and decreased with increasing oil concentration. Deposits of oil at all concentrations significantly suppressed searching efficiency in comparison with control, and searching efficiency in the 1.00% oil treatment was significantly lower than in the 0.25% oil treatment. First predation of P. persimilis on AMO‐contaminated eggs of two‐spotted mite ( Tetranychus urticae Koch) on unsprayed leaf discs was significantly delayed in all oil treatments in comparison with the control. However there was no significant effect on the overall predation rate. In the tests of P. persimilis predation on AMO‐contaminated T. urticae eggs on sprayed leaf discs, the number of first predation occurrences in the first hour was significantly lower in 0.50% and 1.00% oil treatments than in the control. Overall predation rates were significantly reduced by oil but they did not differ significantly among the oil treatments.
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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".