Biology and management of North American cone-feeding<i>Dioryctria</i>species
Bibliographic record
Abstract
Abstract Coneworms,DioryctriaZeller (Lepidoptera: Pyralidae), are destructive pests of conifers across North America, and members of several different species groups present significant pest-management challenges in conifer seed orchards.Dioryctria abietivorellaGrote (abietellagroup) is the most pestiferousDioryctriaspecies in Canada. Despite this status, control tactics are currently limited to broad-spectrum pesticides that threaten non-target species and may result in pesticide resistance. The development of integrated pest management programs targetingDioryctriaspecies will benefit from a conceptual framework on which to base future research. To create this structure, we review the systematics, evolutionary ecology, and management of cone-feeding North AmericanDioryctriaspecies. Current research suggests that many species boundaries are in need of further revision. Major gaps in our understanding ofDioryctriaecology impede the development of integrated pest management tactics. For example, host-generated semiochemicals are important inDioryctriareproduction, although the uses of these cues in host-finding and host acceptance remain unknown. Future research should identify factors that mediate population distribution at landscape (e.g., migration), local (e.g., feeding stimulants), and temporal (e.g., development thresholds) scales.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".