Estimated Abundance of Adult Fall Chum Salmon in the Middle Yukon River, Alaska, 2004
Bibliographic record
Abstract
Mark and recapture data were collected to estimate the abundance of fall chum salmon Onchorhynchus keta during 2004 in the middle Yukon River, above the Tanana River confluence. Weekly stratum estimates of migrating fall chum salmon were generated for a period of approximately eight weeks between 27 July and 21 September 2004. Fish were captured with a single fish wheel at the marking and recovery sites. Color-coded spaghetti tags were applied to 4,166 fish at the marking site. Throughout the season, 25,265 fish were examined for marks at the recovery site using video recordings. The tag status of 273 (1%) fish could not be determined and 197 (<1%) fish were tagged. Using a Darroch estimator, the estimated abundance of fall chum salmon migrating through the mainstem Yukon River in 2004 was 618,579 (SE 60,714) for the sampling period. Our estimate was 85% greater than the 2004 run reconstruction for fall chum salmon in the upper Yukon River. The run reconstruction included the combined total of tributary escapements (Chandalar, Sheenjek, and Fishing Branch rivers), harvest estimates above the study area, and Canadian border passage estimate of fall chum salmon. The difference between the Rampart-Rapids passage estimate and the run reconstruction may be partially attributed to unexpected biological and hydrologic factors during the 2004 field season.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".