The effect of fasting and body reserves on cold tolerance in 2 pit-building insect predators
Bibliographic record
Abstract
Pit-building antlions and wormlions are 2 distantly-related insect species, whose larvae construct pits in loose soil to trap small arthropod prey. This convergent evolution of natural histories has led to additional similarities in their natural history and ecology, and thus, these 2 species encounter similar abiotic stress (such as periodic starvation) in their natural habitat. Here, we measured the cold tolerance of the 2 species and examined whether recent feeding or food deprivation, as well as body composition (body mass and lipid content) and condition (quantified as mass-to-size residuals) affect their cold tolerance. In contrast to other insects, in which food deprivation either enhanced or impaired cold tolerance, prolonged fasting had no effect on the cold tolerance of either species, which had similar cold tolerance. The 2 species differed, however, in how cold tolerance related to body mass and lipid content: although body mass was positively correlated with the wormlion cold tolerance, lipid content was a more reliable predictor of cold tolerance in the antlions. Cold tolerance also underwent greater change with ontogeny in wormlions than in antlions. We discuss possible reasons for this lack of effect of food deprivation on both species' cold tolerance, such as their high starvation tolerance (being sit-and-wait predators).
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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".