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Record W1948653456 · doi:10.1139/cjfas-2012-0491

Large-scale freshwater habitat features influence the degree of anadromy in eight Hood Canal<i>Oncorhynchus mykiss</i>populations

2013· article· en· W1948653456 on OpenAlexvenueno aff
Barry A. Berejikian, Lance Campbell, Megan E. Moore

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersWashington Department of Fish and WildlifeWashington State University
KeywordsFish migrationHabitatSTREAMSJuvenileOtolithEstuaryEcologyFjordFisheryGeographyBiologyOceanographyGeologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Juvenile Oncorhynchus mykiss maternity was determined from otolith strontium:calcium ratios to investigate the degree of anadromy in eight freshwater streams draining to a common fjord. The percentages of O. mykiss parr produced by anadromous females ranged from an annual average of 41.3% (Hamma Hamma River) to 100% (Dewatto River). The proportion of stream habitat available to resident O. mykiss upstream of barriers to anadromous migration explained a significant portion of the variability in maternal life history below barrier falls and was included in each of the five logistic regression models with the lowest AIC scores. Transitional hydrologic profiles, low mean annual temperatures and high mean annual stream flow, common to Olympic Peninsula streams, were each associated with greater proportions of offspring from resident females. Only 2 out of 234 parr from the lowland, rain-driven, low-flow streams of the Kitsap Peninsula were produced by resident females. Thus, large-scale habitat features, and primarily the presence or absence of resident populations above natural barriers to anadromous migration, appeared to shape the degree of anadromy among populations.

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 score0.975
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.016
GPT teacher head0.207
Teacher spread0.191 · 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

Citations30
Published2013
Admission routes1
Has abstractyes

Explore more

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