An age–size reaction norm yields insight into environmental interactions affecting life‐history traits: a factorial study of larval development in the malaria mosquito <i>Anopheles gambiae</i> sensu stricto
Bibliographic record
Abstract
Environmental factors frequently act nonindependently to determine growth and development of insects. Because age and size at maturity strongly influence population dynamics, interaction effects among environmental variables complicate the task of predicting dynamics of insect populations under novel conditions. We reared larvae of the African malaria mosquito Anopheles gambiae sensu stricto (s.s.) under three factors relevant to changes in climate and land use: food level, water depth, and temperature. Each factor was held at two levels in a fully crossed design, for eight experimental treatments. Larval survival, larval development time, and adult size (wing length) were measured to indicate the importance of interaction effects upon population-level processes. For age and size at emergence, but not survival, significant interaction effects were detected for all three factors, in addition to sex. Some of these interaction effects can be understood as consequences of how the different factors influence energy usage in the context of a nonindependent relationship between age and size. Experimentally assessing interaction effects for all potential future sets of conditions is intractable. However, considering how different factors affect energy usage within the context of an insect's evolved developmental program can provide insight into the causes of complex environmental effects on populations.
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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 | 0.001 | 0.003 |
| 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".