Individual-based analyses reveal high repeatability in timing and location of reproduction in lake sturgeon (<i>Acipenser fulvescens</i>)
Bibliographic record
Abstract
Few studies have quantified the repeatability of reproductive decisions by individuals or assessed their relationship with environmental variables over multiple seasons for long-lived iteroparous fish species. Using individual-based data collected for 678 lake sturgeon ( Acipenser fulvescens ) over 8 consecutive years, we evaluated hypotheses regarding spawning periodicity and repeatability of spawning location, spawning time, and environmental cues associated with spawning. At our study site (Upper Black River, northern Michigan, USA), interspawning interval differed between males (2.3 ± 0.08 years) and females (3.7 ± 0.16 years), but was not significantly related to age. Individual spawning behavior was highly repeatable with respect to spawning time (relative day within the spawning season) for both sexes regardless of size or age, but was less repeatable, though still significant, relative to water temperature, river discharge, and lunar phase. Breeding area was also repeatable, with individuals spawning earlier in the season selecting locations further upstream than those spawning later. Repeatability in spawning times and locations suggest that subpopulation differentiation may develop among different spawning groups, even within small and spatially contiguous areas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".