The impacts of repeated cold exposure on insects
Bibliographic record
Abstract
Insects experience repeated cold exposure (RCE) on multiple time scales in natural environments, yet the majority of studies of the effects of cold on insects involve only a single exposure. Three broad groups of experimental designs have been employed to examine the effects of RCE on insect physiology and fitness, defined by the control treatments: 'RCE vs cold', which compares RCE with constant cold conditions; 'RCE vs warm', which compares RCE with constant warm conditions; and 'RCE vs matched cold' which compares RCE with a prolonged period of cold matched by time to the RCE condition. RCE are generally beneficial to immediate survival, and increase cold hardiness relative to insects receiving a single prolonged cold exposure. However, the effects of RCE depend on the study design, and RCE vs warm studies cannot differentiate between the effects of cold exposure in general vs RCE in particular. Recent studies of gene transcription, immune function, feeding and reproductive output show that the responses of insects to RCE are distinct from the responses to single cold exposures. We suggest that future research should attempt to elucidate the mechanistic link between physiological responses and fitness parameters. We also recommend that future RCE experiments match the time spent at the stressful low temperature in all experimental groups, include age controls where appropriate, incorporate a pilot study to determine time and intensity of exposure, and measure sub-lethal impacts on fitness.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".