Eco-immunology in the cold: the role of immunity in shaping the overwintering survival of ectotherms
Bibliographic record
Abstract
The effect of temperature on physiology mediates many of the challenges that ectotherms face under climate change. Ectotherm immunity is thermally sensitive and, as such, environmental change is likely to have complex effects on survival, disease resistance and transmission. The effects of temperature on immunity will be particularly profound in winter because cold and overwintering are important triggers and regulators of ectotherm immune activity. Low temperatures can both suppress and activate immune responses independent of parasites, which suggests that temperature not only affects the rate of immune responses but also provides information that allows overwintering ectotherms to balance investment in immunity and other physiological processes that underlie winter survival. Changing winter temperatures are now shifting ectotherm immunity, as well as the demand for energy conservation and protection against parasites. Whether an ectotherm can survive the winter will thus depend on whether new immune phenotypes will shift to match the conditions of the new environment, or leave ectotherms vulnerable to infection or energy depletion. Here, we synthesise patterns of overwintering immunity in ectotherms and examine how new winter conditions might affect ectotherm immunity. We then explore whether it is possible to predict the effects of changing winter conditions on ectotherm vulnerability to the direct and indirect effects of parasites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".