Temporal Changes and Sexual Differences in Spatial Distribution of Burbot in Lake Erie
Bibliographic record
Abstract
Abstract We used GIS mapping techniques to examine capture data for Burbot Lota lota from annual gill‐net surveys in Canadian waters of Lake Erie during late August and September 1994–2011. Adult males were captured over a larger area (3–17% for ≥20% maximum yearly catch [MYC]) than adult females. More males than females were caught in the gill nets in 14 of the 15 study years. Collectively, these results support a hypothesis of greater activity by adult males during summer, when Burbot are actively feeding. The area of capture contracted by more than 60% (for ≥20% MYC) for both sexes during the time period, which is consistent with the documented decrease of the Burbot population in the lake. The sex ratio (females: males) varied over the time series but declined steadily from 0.97 in 2001 to 0.59 in 2011. The overlap in the capture areas of adult males and females was scale dependent. The depth distribution at which adult Burbot were caught did not change over the time series, and there was no difference in the median depths (about 30 m) at which adult male and female Burbot were caught. The last results are consistent with the Burbot's reliance on coldwater habitats. Additional research is recommended, including telemetry to describe daily and seasonal movements and assessment of gender bias in active and passive capture gear.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".