Relative Importance of Water Temperature, Water Level, and Lunar Cycle to Migratory Activity in Spawning‐Phase Sea Lampreys in Lake Ontario
Bibliographic record
Abstract
Abstract We analyzed historical trapping records from six Lake Ontario tributaries to (1) compare the relative importance of water temperature, water level, and lunar cycle to migratory activity in upstream‐migrating sea lampreys Petromyzon marinus and (2) determine whether the relative importance of these variables differs among streams. We found significant stream‐dependent differences in the relative importance of the environmental variables. Water temperature was the best predictor of migratory activity in all six streams. The seasonal distribution of migratory activity was related to mean stream temperature, with an estimated peak migration temperature of approximately 15°C. Changes in stream temperature were equally as important. Migratory activity was stimulated when mean stream temperature increased between consecutive days and was suppressed when mean stream temperature decreased between consecutive days. Water level was a reliable predictor of migratory activity only in the two smallest streams. We hypothesize that high water levels may increase migratory activity in small streams by making them more noticeable. There was no evidence to support either a circumlunar rhythm or gravitational influence on migratory activity. However, because we did not account for cloud cover or the presence of artificial light sources, we cannot exclude the possibility that nighttime light levels influence migratory activity. Our findings provide a set of rules for coarsely projecting migratory activity in upstream‐migrating sea lampreys.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".