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Record W4366976877 · doi:10.1139/cjz-2023-0039

From color to shape: ontogenetic shifts in traits of the freshwater crab <i>Dilocarcinus pagei</i> (Brachyura: Trichodactylidae)

2023· article· en· W4366976877 on OpenAlexvenueno aff
Alexandre Ribeiro da Silva, Caio Santos Nogueira

Bibliographic record

VenueCanadian Journal of Zoology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyCarapaceClawFreshwater crabOntogenyZoologyAdaptation (eye)VelvetCrustaceanSexual dimorphismSexual selectionDecapodaEcology

Abstract

fetched live from OpenAlex

Crustaceans usually undergo a series of changes after the puberty molt. These changes are often associated with size increases in the body and in structures such as the abdomen and claws so that they can achieve higher reproductive fitness. These morphological changes allow the animal to fight, court, and signal for its conspecific with better performance. To compare ontogenetic changes, we used the freshwater crab Dilocarcinus pagei Stimpson, 1851 as a model. We analyzed differences in carapace and claw shape, force generation (via the apodeme area), morphological integration of claws, and color changes among demographic groups. Adult crabs had an increase in claw and carapace size followed by a shape change that makes the claws more robust. In addition, the animals changed from a dark brown coloration in juveniles to a dark red coloration in adult males, while adult females presented a dark red-brown coloration. Presumably, phenotypic changes may enhance crabs’ ability to obtain different food sources, as well as fight for sexual partners, and manipulate females during courtship. Color changes can be a strategy by which adult males can signal to females, while the dark brown coloration of juveniles can help in camouflage in the substrate.

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)0.000
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.013
GPT teacher head0.211
Teacher spread0.198 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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Same venueCanadian Journal of ZoologySame topicCrustacean biology and ecologyFrench-language works237,207