Bibliographic record
Abstract
Abstract A review of insect adaptations for resistance to cold and for life-cycle timing reveals the complexity of the adaptations and their relationships to features of the environment. Cold hardiness is a complex and dynamic state that differs widely among species. Surviving cold depends on habitat choice, relationships with ice and water, and synthesis of a variety of cryoprotectant molecules. Many aspects are time-dependent and are integrated with other factors such as taxonomic affinity, resource availability, natural enemies, and diapause. Timing adaptations reflect the fact that all environments change over many different time frames, from days to thousands of years. Environments differ in severity and in the extent, nature, variability, and predictability of change, as well as in how reliably cues indicate probable conditions in the future. These differences are reflected by a wide range of insect life-cycle systems, life-cycle delays, levels of responsiveness to various environmental signals, genetic systems, and circadian responses. In particular, the degree of environmental change, its predictability on different time frames, and whether it can be monitored effectively dictate the balance between fixed and flexible timing responses. These same environmental features have to be characterized to understand cold hardiness, but this has not yet been done. Therefore, the following key questions must be answered in order to put cold hardiness into the necessary ecological context: How much do conditions change? How consistent is the change? How reliable are environmental signals?
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".