Distribution and Population Characteristics of Burbot in the Missouri River, Montana Based on Hoop Net, Cod Trap, and Slat Trap Captures
Bibliographic record
Abstract
Although burbot Lota lota are native to Montana, little is known about their distribution, life history, and ecology. The objectives of this study were to deter- mine the distribution and population characteristics of burbot in the upper Missouri River basin in north-central Montana and to compare sampling efficiency of hoop nets, cod traps, and slat traps. Hoop nets and cod traps were fished in the Missouri River during March 2005 and 2006, and slat traps were fished during March 2006. In total, hoop nets were fished 572 net nights, cod traps for 94 net nights, and slat traps for 92 net nights. Catch rates of hoop nets and cod traps were higher in 2005 than in 2006, and catch rates of all gear types were higher in the upstream half of the study area. Mean section hoop-net catch rates exhibited a significant inverse relationship with increasing distance downstream from Holter Dam, while catch rates for other gear types did not. Catch rates were not significantly different ( P ≥ 0.05) among gear types. The size (length and weight) and condition (relative weight) of burbot sampled was significantly ( P ≤ 0.05) different among gear types. Length, weight, and relative weight were higher for burbot sampled in hoop nets and cod traps than those sampled in slat traps. Slat traps were effective at sampling small (≤300 mm) burbot. Although most (80%) burbot were recaptured within 10 km of where they were tagged, three burbot moved more than 32 km. We hypothesize that the distribution of burbot in our study reach has changed and relative abundance has increased due to the cumulative effect of upstream reservoirs (Canyon Ferry, Hauser, and Holter) by decreasing the downstream water temperature regimen.cilitated 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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".