An updated review of cold shock and cold stress in fish
Bibliographic record
Abstract
Temperature is critical in regulating virtually all biological functions in fish. Low temperature stress (cold shock/stress) is an often-overlooked challenge that many fish face as a result of both natural events and anthropogenic activities. In this study, we present an updated review of the cold shock literature based on a comprehensive literature search, following an initial review on the subject by M.R. Donaldson and colleagues, published in a 2008 volume of this journal. We focus on how knowledge on cold shock and fish has evolved over the past decade, describing advances in the understanding of the generalized stress response in fish under cold stress, what metrics may be used to quantify cold stress and what knowledge gaps remain to be addressed in future research. We also describe the relevance of cold shock as it pertains to environmental managers, policymakers and industry professionals, including practical applications of cold shock. Although substantial progress has been made in addressing some of the knowledge gaps identified a decade ago, other topics (e.g., population-level effects and interactions between primary, secondary and tertiary stress responses) have received little or no attention despite their significance to fish biology and thermal stress. Approaches using combinations of primary, secondary and tertiary stress responses are crucial as a research priority to better understand the mechanisms underlying cold shock responses, from short-term physiological changes to individual- and population-level effects, thereby providing researchers with better means of quantifying cold shock in laboratory and field settings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".