Temperature constraints shaped the migration routes of mackerel (Scomber scombrus) in the Black Sea
Bibliographic record
Abstract
Conventional narratives explain fish migrations in term of requirements (food, mates, habitats, etc.), with adequate temperatures being optional. Here, using the example of a (commercially extinct) stock of Black Sea mackerel (Scomber scombrus), we suggest that seasonal migrations are driven by seasonal temperature cycles. Therein, temperature acts as a constraint determining where the fish can be at any given time, and not a one of several factors which they would consider when choosing between alternative migration routes. Generalizing, we suggest that temperature should generally be an explicit part of hypotheses about the migratory behaviours of marine fishes. For illustration of what may occur when this is not the case, it is suggested that the non-consideration of temperature in a model of North Atlantic mackerel migration may have led, among the researchers concerned, to a sense of complacency with respect to the climate change-induced changes in the phenology of this fish in the North Atlantic, whose distribution and migration are misleadingly seen as “stochastic”.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".