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Record W2061838608 · doi:10.1139/f06-011

Temperature-dependent growth of the blue crab (<i>Callinectes sapidus</i>): a molt process approach

2006· article· en· W2061838608 on OpenAlexvenueno aff
Bryce J. Brylawski, Thomas J. Miller

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsnot available
FundersHudson River Foundation
KeywordsCallinectesCarapaceMoultingCrustaceanPortunidaeJuvenileOverwinteringMudaBiologyFisheryGrowth modelDecapodaEcologyMathematics

Abstract

fetched live from OpenAlex

Crustaceans display discrete and biphasic growth as a result of the molting process, so the traditionally used von Bertalanffy growth model does not capture well the phenomena associated with molting-based growth. A molt-process model can predict crustacean growth, including the temperature dependence of intermolt period that can produce the extended overwintering phenomena during which growth ceases. This study parameterized a molt-process model for the blue crab (Callinectes sapidus; Portunidae). Crab growth histories were observed for individual crabs held in field enclosures and temperature-controlled, recirculating tanks. A growth-based temperature of torpor (T min ) of 10.8 °C was determined. A mean growth per molt of 119.5% increase in carapace width was observed. The average intermolt period observed was 536 ± 231 degree-days. The predictive ability of these growth parameter estimates was evaluated against growth observed in the field based on data on interannual changes in size frequencies of crabs from a winter dredge survey. The evaluated model was used to explore recruitment timing in warm (1996) and cold (1998) years. A 10% shift in the timing of juvenile crabs becoming available for legal exploitation was predicted from the simulations.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.985

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 studies0.0000.002
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 head0.008
GPT teacher head0.187
Teacher spread0.180 · 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

Citations75
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicCrustacean biology and ecologyFrench-language works237,207