Burbot: Ecology, Management, and Culture
Bibliographic record
Abstract
Abstract.—Burbot Lota lota populations collapsed in four of the five Laurentian Great Lakes between 1930 and the early 1960s. Collapses in Lakes Michigan, Huron, and Ontario were associated with sea lamprey Petromyzon marinus predation, whereas the collapse in Lake Erie was likely due to a combination of overexploitation, decreased water quality, and habitat degradation. We examined time series for burbot population density in all five lakes extending as far back as the early 1970s to present time and characterized the long-term trends after the initial collapses. Burbot population density in Lake Superior has remained relatively low and stable since 1978. Recovery of the burbot populations occurred in Lakes Michigan and Huron during the 1980s and in Lake Erie during the 1990s. Control of sea lampreys was a requirement for recovery of burbot populations in these three lakes. Declines in alewife Alosa pseudoharengus abundance appeared to be a second requirement for burbot recovery in Lakes Michigan and Huron. Alewives have been implicated in the decline of certain Great Lakes fish stocks that have pelagic larvae (e.g., burbot) by consuming the pelagic fry and possibly by outcompeting the fry for food. Relatively high populations of adult lake trout Salvelinus namaycush compared to burbot served as a buffer against predation by sea lampreys in Lakes Huron and Erie, which facilitated recovery of the burbot populations there. Although sea lampreys have been controlled in Lake Ontario, alewives are probably still too abundant to permit burbot recovery.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".