Evaluation of Sampling Methodology for Determining the Phenology, Relative Density, and Dispersion of Western Flower Thrips (Thysanoptera: Thripidae) in Nectarine Orchards
Bibliographic record
Abstract
Western flower thrips, Frankliniella occidentalis (Pergande), cause serious economic damage to nectarines in the Okanagan and Similkameen Valleys, British Columbia, Canada. We evaluated several sampling methods for western flower thrips for their precision and ability to predict general population trends. Beating of branches, flicking of buds, and visual estimation methods were not accurate for estimating numbers of thrips in nectarine buds. Thrips caught on sticky cards indicated general population trends, but were less efficient than collecting nectarine buds and counting thrips. Searching for thrips from buds in the field underestimated the density of both adults and larvae, and for adults, underestimated the proportion of the pale morph of western flower thrips. Dispersion patterns of thrips populations among orchards were either random or aggregated dependent on the development stage of the nectarine buds.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".