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Record W4413881404 · doi:10.1093/najfmt/vqaf065

Genetic mixed-stock analysis reveals evidence of adverse effects on fall Chum Salmon tagged in the Yukon River

2025· article· en· W4413881404 on OpenAlexaboutno aff
Blair G. Flannery, Randy J. Brown, John H. Eiler

Bibliographic record

VenueNorth American Journal of Fisheries Management · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersU.S. Fish and Wildlife Service
KeywordsFisheryStock (firearms)Environmental scienceGeographyBiologyArchaeology

Abstract

fetched live from OpenAlex

ABSTRACT Objective In 1999, radiotelemetry data suggested that 25% of the fall Chum Salmon Oncorhynchus keta migration in the Yukon River above the confluence with the Tanana River remained in the Yukon Flats, an extensive, highly braided main-stem area of the Yukon River. Our objective was to determine whether this represents Chum Salmon spawning within main-stem reaches of the Yukon Flats or a handling effect impacting fish from stocks destined for spawning areas farther upstream. Methods To assess the validity of the radiotelemetry-based stock composition estimates, we conducted genetic mixed-stock analysis on tissue samples collected from radio-tagged fish. Results Nonoverlapping CIs provided evidence that radiotelemetry and genetic stock composition estimates were different for upper Yukon River stocks. The genetic-based composition estimate (42%) for upper Yukon River stocks was greater than the radiotelemetry estimate (18%). Overlapping CIs provided no evidence that the estimates from the two methods were different for the U.S. border and upper Porcupine River. For fish last located by radiotelemetry in the Yukon Flats, genetic stock composition estimates classified most (86%) as upper Yukon River stocks. The likelihood ratio test revealed strong evidence that genetic stock composition estimates were different between fish tracked to terminal locations and those not tracked to terminal locations. A greater proportion of fish from the upper Yukon River was present in the mixture of fish that did not reach terminal locations, whereas a greater proportion of fish from the U.S. border was present in the terminal mixture. The assignment test revealed strong evidence that radiotelemetry samples had a higher proportion of misassignments than known-origin samples. Most (64%) misassignments involved fish that were genetically assigned to the upper Yukon River. Conclusions These results indicate that upper Yukon River fish in the radiotelemetry study suffered from residual handling effects and were less likely to reach their natal spawning grounds.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.224
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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