Documentation of Annual Spawning Migrations of Anadromous Coregonid Fishes in a Large River using Maturity Indices, Length and Age Analyses, and CPUE
Bibliographic record
Abstract
Coregonid fi shes contribute to major food fi sheries throughout the Yukon River drainage in northwest North America. Research and management activities related to these coregonid fi shes, however, have been minimal because of the commercial and international focus on Pacifi c salmon Oncorhynchus spp. populations that share the drainage. We studied fi ve coregonid species at a fi sh- wheel sampling site 1,200 km from the Bering Sea. They were inconnu Stenodus leucichthys, broad whitefi sh Coregonus nasus, humpback whitefi sh C. clupeaformis, least cisco C. sardinella, and Bering cisco C. laurettae. Otolith chemistry studies have shown that anadromy is a common or prevailing life history strategy for all fi ve species at our fi sh-wheel sampling site. Radio telemetry studies revealed major spawning habitats for four species in the Yukon Flats, an extensive braided region of the river 1,600 to 1,700 km upstream from the Bering Sea. The objectives of this study were to document the demographic qualities of migrating coregonids at the fi sh-wheel sampling site and to defi ne seasonal periods of relative abundance based on daily catch rates. Maturity indices indicated that nearly all fi sh were mature and preparing to spawn. Minimum lengths and ages of maturity ranged from low values of 23 cm and 2 years for least cisco, to high values of 58 cm and 7 years for inconnu. A video system on the sampling fi sh wheel provided seven years of species-specifi c catch rate data that we used to identify the timing of seasonal spawning migrations for all species except least cisco.
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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".