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Record W3189578888 · doi:10.51492/cfwj.107.7

The distribution of anadromy and residency in steelhead/rainbow trout in the Eel River, northwestern California

2021· article· en· W3189578888 on OpenAlexaff
Bret C. Harvey, Rodney J. Nakamoto, Adam J.R. Kent, Christian E. Zimmerman

Bibliographic record

VenueCalifornia Fish and Wildlife Journal · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsIONICS Mass Spectrometry (Canada)
FundersU.S. Geological Survey
KeywordsRainbow troutFish migrationFisheryJuvenileFish <Actinopterygii>OtolithDistribution (mathematics)TroutRange (aeronautics)Environmental scienceGeographyEcologyBiology

Abstract

fetched live from OpenAlex

To inform management and conservation of the species, we investigated the distribution of anadromy and residency of steelhead/rainbow trout (Oncorhynchus mykiss) in the Eel River of northwestern California. We determined maternal anadromy versus residency for 106 juvenile O. mykiss using otolith microchemistry. To attempt to relate patterns of anadromy with environmental factors known to influence its distribution in O. mykiss in other places, fish were collected from 52 sites throughout the drainage covering a range of stream size (0.1–7.7 m3/s estimated mean annual run-off) and distance from the ocean (23–219 km). Sixty-one of 91 fish sampled below prospective barriers had anadromous mothers, while 1 of 15 fish sampled above barriers had an anadromous mother. We did not detect any influence of stream size or distance from the ocean on the occurrence of anadromy. Fish with resident mothers were found at 21 of 46 sites below barriers. The current broad distribution of fish with resident mothers indicates the importance of maintaining freshwater conditions suitable for resident adults and juveniles age-1 and older, such as preserving dry-season streamflows.

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)0.000
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 score0.095
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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