Metabolism and energy supply below the critical thermal minimum of a chill-susceptible insect
Bibliographic record
Abstract
When exposed to temperatures below their critical thermal minimum (CT(min)), insects enter chill-coma and accumulate chilling injuries. While the critical thermal limits of water-breathing marine animals may be caused by oxygen- and capacity-limitation of thermal tolerance (OCLT), the mechanisms are poorly understood in air-breathing terrestrial insects. We used thermolimit respirometry to characterize entry into chill-coma in a laboratory population of fall field crickets (Gryllus pennsylvanicus). To detect potential oxygen limitation, we quantified muscle ATP, lactate and alanine concentrations in crickets following prolonged exposure to 0°C (a temperature that causes chill-coma, chilling injury and eventual death). Although there was a sharp (44%) drop in the rate of CO(2) emission at the CT(min) and spiracular control was lost, there was a low, continuous rate of CO(2) release throughout chill-coma, indicating that the spiracles were open and gas exchange could occur through the tracheal system. Prolonged exposure to 0°C caused muscle ATP levels to increase marginally (rather than decrease as OCLT would predict), and there was no change in muscle lactate or alanine concentration. Thus, it appears that insects are not susceptible to OCLT at low temperatures but that the CT(min) may instead be set by temperature effects on whole-animal ion homeostasis.
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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".