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Record W2783416392 · doi:10.1139/cjz-2017-0050

Effect of geographic location and sexual dimorphism on shield shape of the Red Sea hermit crab <i>Clibanarius signatus</i> using the geometric morphometric approach

2018· article· en· W2783416392 on OpenAlexvenueno aff
Tarek G. Ismail

Bibliographic record

VenueCanadian Journal of Zoology · 2018
Typearticle
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsnot available
Fundersnot available
KeywordsSexual dimorphismBiologyIntertidal zoneEcologyLittoral zoneHabitatZoology

Abstract

fetched live from OpenAlex

The hermit crab Clibanarius signatus Heller, 1861 inhabits varied intertidal habitats of the Red Sea coast, such as rocky shores and mangrove littoral salt marshes. Shield-shape variation among three populations of C. signatus was analyzed with geometric morphometric methods. Shape variation was studied through multivariate analyses using configurations aligned by the generalized Procrustes analysis. Shape variation was explored through principal component analysis. The ordination of the populations and the sexes was investigated using discriminant analysis of canonical variables. Centroid size, as a measure of overall size, was used to estimate size variation among the three populations and the sexes. The results revealed the presence of shield-size variation among the three populations and confirmed the size sexual dimorphism in two populations. Moreover, the analysis revealed the occurrence of two morphotypes based on a covariation between shield shape and shape of occupied shells. The geographic distance was not a good predictor of shield shape. Cross-validation analyses correctly reclassified more than 70% of individuals and 66% of sexes to their correct group. It was suggested that association in shield-shell shape could be the result of the phenotypic plasticity of this species.

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)0.002
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 score0.026
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.259
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

Citations12
Published2018
Admission routes1
Has abstractyes

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