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Record W1880422363 · doi:10.1139/cjfas-2015-0176

A hump-shaped relationship between migration distance and adult pink salmon morphology suggests interactive effects of migration costs and bear predation

2015· article· en· W1880422363 on OpenAlexvenueno aff
Genki Sahashi, Taku Yoshiyama

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsPredationOncorhynchusHabitatBiologyEcologyFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

We examined the relationship between environmental factors of a spawning habitat and body shape at maturity in 16 pink salmon (Oncorhynchus gorbuscha) populations. The divergence vector (indicator of body depth and head size development) in both sexes was significantly correlated with distance from the sea and was described by a hump-shaped relationship. An exaggerated body shape was most developed at mid-distance from the sea and less developed both near and far from the sea. The observed frequency of bears decreased significantly with distance from the sea, implying that bear predation on salmon is most intense near the sea. Therefore, our results imply that shape-selective predation by bears affects the shape of pink salmon in rivers where the spawning habitat is near the sea and that migration costs inhibit development of an exaggerated body depth and head size in salmon in rivers where the spawning habitat is far from the sea.

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)0.002
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

Explore more

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