White pine weevil performances in relation to budburst phenology and traumatic resin duct formation in Norway spruce
Bibliographic record
Abstract
Abstract 1 As the phenological window hypothesis was reported to be significant in influencing the fitness of many herbivores feeding on tree foliage, could it also explain the performance of an insect such as the white pine weevil Pissodes strobi mainly attacking the bark phloem of conifers? 2 Under field conditions, adult weevils were caged on Norway spruce trees presenting a natural variation in their shoot growth phenology. 3 We evaluated white pine weevil biological performances, including oviposition, the number of emerged insects, survival, adult mean weight and tree defense responses as reflected by the production of induced resin canals. 4 None of the white pine weevil biological parameters was significantly affected by Norway spruce phenology. 5 The number of eggs per hole, the number of oviposition holes per leader, the number of emerged adults and their mean weight were not affected by host phenology. 6 The intensity of the traumatic response observed was variable and not correlated with budburst phenology. 7 Trees with higher traumatic responses, forming two or more layers of traumatic ducts, had lower adult emergence and estimated survival. 8 The distance between the first layer of traumatic resin ducts and the start of the annual ring was not correlated with the number of emerged weevils. 9 Norway spruce, which is an exotic tree in North America and a relatively recent host for the white pine weevil, might not possess the defense mechanisms necessary to fight off the white pine weevil.
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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".