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Record W2021463779 · doi:10.1139/f00-190

Heritability of fluctuating asymmetry for multiple traits in chinook salmon (<i>Oncorhynchus tshawytscha</i>)

2000· article· en· W2021463779 on OpenAlexfundvenueno aff
Colleen A Bryden, Daniel D. Heath

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2000
Typearticle
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHeritabilityChinook windOncorhynchusFluctuating asymmetryBiologySalmonidaeZoologyFisheryFish <Actinopterygii>Evolutionary biologyRainbow trout

Abstract

fetched live from OpenAlex

The heritability of fluctuating asymmetry (FA) as an indicator of developmental instability is of interest to evolutionary and conservation biologists and is the subject of ongoing controversy. This study examined the inheritance of FA in two groups of fish: domestic chinook salmon (Oncorhynchus tshawytscha) mated in a full-sib design and domestic and wild chinook salmon mated in a half-sib design. Eight traits were measured on the right and left sides of each fish: eye diameter, head length, maxillary length, branchiostegal ray number, pectoral and pelvic fin ray number, and upper and lower gill raker number on the first gill arch. Narrow-sense heritabilities were calculated from parent-offspring regressions for the first group and using sib analysis for the second group. Our data represent the largest breeding program designed to detect heritability of FA in fish reported to date. We found no significant heritability of FA for any of the individual traits examined or for a composite FA index. Our results indicate that FA estimates in chinook salmon will not be confounded by appreciable additive genetic contributions and thus can be reliably used as an environmental and genetic stress indicator.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.460
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0000.000

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 head0.040
GPT teacher head0.269
Teacher spread0.229 · 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 teacher head, 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

Citations20
Published2000
Admission routes2
Has abstractyes

Explore more

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