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Record W2017675121 · doi:10.1139/f99-243

Declivity in steelhead (<i>Oncorhynchus mykiss</i>) recruitment at the Keogh River over the past decade

2000· article· en· W2017675121 on OpenAlexvenueno aff
Bruce R. Ward

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersMinistry of Environment
KeywordsFisheryRainbow troutOncorhynchusStock (firearms)BiologyEnvironmental scienceFish <Actinopterygii>Geography

Abstract

fetched live from OpenAlex

Survival and return of unharvested winter-run steelhead (Oncorhynchus mykiss) at the Keogh River, British Columbia, declined abruptly and remained persistently low after 1990. Adult returns averaged 1168 fish from 1976 to 1990 but were significantly lower from 1991 to 1998 (mean 223). Forty wild females returned to the 35-km river in 1995-1996, 20 in 1996-1997, and <10 in 1997-1998. The positive linear relationship between smolts and returns was significantly lower after 1990 and no longer correlated with smolt size. Smolt-to-adult survival averaged 15% (1976 to 1989) but recently averaged 3.5% (1990 to 1995). Smolt number steadily declined to <1000 by 1998 from an average annual count of 7000. Smolts per spawner from 1991 to 1994 were, on average, 70% lower than previous estimates based on the same spawner abundance. Recruitment scenarios based on survival histories during freshwater and marine life stages indicated that adult recruits are currently below replacement and unsustainable if conditions continue or worsen. Factors influencing steelhead in the ocean and freshwater are likely similar for other salmonids; harvest impacts must be reduced and appropriate stock rebuilding measures implemented.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.877
Threshold uncertainty score0.244

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.235
Teacher spread0.209 · 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

Citations68
Published2000
Admission routes1
Has abstractyes

Explore more

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