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TARSAL ASYMMETRY, NUTRITIONAL CONDITION, AND SURVIVAL IN WATER BOATMEN (CALLICORIXA VULNERATA)

2001· article· en· W2179924082 on OpenAlexafffund
Patrik Nosil, T. E. Reimchen

Bibliographic record

VenueEvolution · 2001
Typearticle
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFluctuating asymmetryBiologyForagingPopulationTraitZoologyDemographyEcology

Abstract

fetched live from OpenAlex

Fluctuating asymmetry (FA) has been used as a measure of developmental stability and may indicate individual phenotypic or genotypic quality. Using water boatmen (Callicorixa vulnerata) from a natural population, we examined the relationship between tarsal FA (tarsal spine number, tarsal length) and indices of body condition in two habitats. We used body weight and residual body weight (controlling for body length) as indices of condition because experimental food deprivation in water boatmen led to a reduction in each. We detected a negative relationship between FA and both indices of condition in two ecologically distinct pond habitats. We predicted this association was due to a negative relationship between FA and competitive feeding ability. Consequently, we examined associations between survival time and tarsal FA in C. vulnerata under resource-limited laboratory conditions. Univariate analyses revealed a negative correlation between survival and tarsal FA in each trait. Inclusion of survival time, body length, gender, tarsal spine number, tarsal length, and measures of FA into multivariate analyses revealed a negative correlation between survival and FA. Individuals with the greatest survival had higher nutritional condition than individuals that succumbed early in the experiment. Asymmetric individuals may suffer a foraging handicap as a result of the use of tarsi in feeding or they may be of poor genetic quality. Our results suggest elevated FA may limit resource acquisition and are consistent with the use of FA as a measure of fitness.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.030
GPT teacher head0.290
Teacher spread0.260 · 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 designTheoretical or conceptual
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

Citations38
Published2001
Admission routes2
Has abstractyes

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