Potential for pheromone-baited traps to predict seed loss caused by <i>Contarinia oregonensis</i> (Diptera: Cecidomyiidae)
Bibliographic record
Abstract
Abstract In seed orchards of Douglas-fir, Pseudotsuga menziesii (Mirbel) Franco (Pinaceae), located in Washington State and Oregon, United States, we tested whether catches of male Douglas-fir cone gall midges, Contarinia oregonensis Foote, in pheromone-baited traps can be used to predict the extent of galled scales (= seed loss at harvest) caused by developing larvae. In 2000, 27 experimental blocks (4–7 ha each) were selected. In each block we recorded mean numbers of (i) male C. oregonensis captured in 20 pheromone-baited Wing traps, (ii) egg-infested scales in up to 50 conelets in early spring, and (iii) galled scales in up to 50 cones in late summer. In 2001, the experiment was repeated with 20 Delta traps in each of 26 experimental blocks. Moreover, catches of C. oregonensis and nontarget insects in Delta traps and Wing traps were compared in one additional orchard block in 2001. In both years there were positive correlations between mean numbers of egg-infested and galled scales and between mean numbers of captured male C. oregonensis and mean numbers of both egg-infested and galled scales, particularly when only experimental blocks with ≥50% of trees bearing at least 5 conelets were considered. Our results suggest that 4 or 2 captured male C. oregonensis in Wing or Delta traps, respectively, warrant insecticidal control of C. oregonensis. Delta traps, which captured fewer nontarget insects, would be more suitable than Wing traps for operational implementation of this technology.
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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 | 0.001 |
| 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".