Factors affecting head capsule development in field populations of<i>Altica sylvia</i>(Coleoptera: Chrysomelidae)
Bibliographic record
Abstract
Abstract Traits such as larval growth rate and head capsule width are often measured in economically important insects to determine their developmental stage. However, these traits have the potential to vary between genotypes or in response to several ecological factors. To determine whether geographic or ecological factors cause variability in the head capsule width ofAltica sylviaMalloch (Coleoptera: Chrysomelidae), and to verify whether measures of head capsule width are adequate to identify larval instars in this species,A. sylvialarvae were recovered from 35 fields ofVaccinium angustifoliumAiton (lowbush blueberry; Ericaceae) of eastern New Brunswick, Canada. The distribution of head capsule widths varied in response to accumulated degree-days,A. sylvialarval density, and latitude. An overlap between measures of head capsule width of first-instar and second-instar larvae in fields supporting a high density ofA. sylvialarvae suggested that intraspecific competition caused a reduction in larval growth rate that affected head capsule development and may have induced developmental polymorphism. Based on these results, we stress that the sampling protocol of studies conducted to determine head capsule width intervals in a species should include diverse ecological settings as well as several locations within the range of the species.
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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 | 0.000 |
| 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".