Stock Characteristics of Humpback Whitefish and Least Cisco in the Chatanika River, Alaska
Bibliographic record
Abstract
Overharvest of humpback whitefish (Coregonus pidschian) and least cisco (C. sardinella) in the Chatanika River, Alaska, during the late 1980s led to collapsed stocks and closure of the fishery. We evaluated the stock characteristics of these two species to determine the extent of recovery. A total of 3207 humpback whitefish and 2766 least cisco were captured during their fall spawning migration in 2008. Humpback whitefish ranged from 188 to 583 mm in fork length (FL) and encompassed ages 5 to 29 years, while least cisco ranged from 215 to 425 mm in FL and their ages ranged from 3 to 14 years. Patterns in growth and length-at-age were similar for both species, and annual mortality rates were 31% for humpback whitefish (age 11 and older) and 44% for least cisco (age 9 and older). Population attributes were within the ranges observed for other North American stocks of humpback whitefish and least cisco. Although the humpback whitefish in the Chatanika River have stock attributes that are consistent with low exploitation and this species appears to have recovered, the least cisco in the river still exhibit many attributes that suggest the cisco stock has not fully recovered. The results of this study indicate that the current allowable harvest limit of 2000 whitefish is cautious and appears to be sustainable.
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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 | 0.000 |
| 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".