Abundance and Run Timing of Adult Salmon in Gisasa River, Koyukuk National Wildlife Refuge, Alaska, 2004
Bibliographic record
Abstract
During 2004, a resistance board weir was used to record escapement information for Chinook Oncorhynchus tshawytscha and chum salmon O. keta in the Gisasa River, a tributary of the Koyukuk River, Alaska. An estimated total of 1,774 Chinook salmon migrated through the weir. Five age groups were identified from 540 Chinook salmon sampled, with age 1.2 (39%) dominating. The sex ratio was 31% female and 69% male. The mean length for 181 females was 835 mm, range 560-985 mm, and the mean length for 359 males was 648 mm, range 340-920 mm. An estimated total of 37,851 chum salmon migrated through the weir. Three age groups were identified from 724 chum salmon sampled, with age 0.3 (75%) dominating. The sex ratio was 44% female and 56% male. The mean length for 357 females was 553 mm, range 470-630 mm, and the mean length for 367 males was 588 mm, range 480-680 mm. The most abundant non-salmon species was longnose sucker Catostomus catostomus (N=29), followed by Arctic grayling Thymallus arcticus (N=23), whitefish (Coregoninae; N=21), and northern pike Esox lucius (N=11). Chinook and chum salmon escapement counts from this portion of the Koyukuk River drainage assist fisheries managers in making in-season decisions during the Yukon River commercial and subsistence fishing seasons, provide post-season evaluation of various management practices, and assist in developing future run projections.
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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 | 0.001 | 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".