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Variation in safety factors of claws within and among six species of Cancer crabs (Decapoda: Brachyura)

2000· article· en· W2152721271 on OpenAlexafffund
Graeme Taylor, A. Richard Palmer, Anise Barton

Bibliographic record

VenueBiological Journal of the Linnean Society · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsClawBiologyBitingInterspecific competitionZoologyDecapodaAnatomyEcologyCrustacean

Abstract

fetched live from OpenAlex

To better understand how safety factors of biological structures evolve, we examined the frequency of claw failure, and the intra- and interspeci®c patterns of variation in maximum biting force and breaking strength in the claws of six species of Cancer (Linnaeus) crabs that live in sympatry along the coast of the northeastern Paci®c: C. antennarius, C. branneri, C. gracilis, C. magister, C. oregonensis and C. productus. Although the breakage frequencies in natural populations were similar among species ( » 6%), they were higher than predicted based on failure probabilities calculated from laboratory measurements of biting force and breaking strength for healthy pristine claws. The incidence of claw damage was correlated with the degree of wear, suggesting that claws later in the intermolt interval were more likely to fail. Within species, safety factors increased from 3.1 to 4.6 with increasing instar number due primarily to a decline in muscle stress (force per unit area of apodeme). Surprisingly, the lower maximum muscle stress generated by later instars appeared to be due to behavioral restraint, since it was not accompanied by relatively lower muscle mass. In addition, among individuals of the same claw size, lower breaking forces were correlated with lower maximum biting force, and both were correlated with lighter cuticle and closer muscle mass, suggesting

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.233
Teacher spread0.214 · 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.

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
Published2000
Admission routes2
Has abstractyes

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