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Record W2057015517 · doi:10.1577/t07-079.1

Longevity and Change in Shell Condition of Adult Male Snow Crab <i>Chionoecetes opilio</i> Inferred from Dactyl Wear and Mark‐Recapture Data

2008· article· en· W2057015517 on OpenAlexaffabout
Duane Barros da Fonseca, Bernard Sainte‐Marie, François Hazel

Bibliographic record

VenueTransactions of the American Fisheries Society · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsFisheries and Oceans Canada
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsLongevityPopulationBiologySnowMark and recaptureZoologyFisheryEcologyDemographyGeographyMeteorology

Abstract

fetched live from OpenAlex

Abstract Postmolt longevity and changes in the shell condition and body integrity of male snow crab Chionoecetes opilio after their terminal molt were assessed through a mark‐recapture experiment and population censuses in a commercially unfished locality of eastern Canada. The experiment explored the value of dactyl wear as a quantitative measure and shell condition (SC; measured on a five‐stage scale) as a relative index of shell age. Males were recaptured up to 6 years after release. Much of the extensive variation in observed dactyl wear was explained by time at liberty (Δ t ) and male size, and the extent of change in SC was positively correlated with Δ t . The conservative wear‐based estimate of male longevity was 7.7 years, a value 1‐3 years greater than previously estimated. Dactyl wear and recapture data confirmed that SC is a relative, albeit rough, index of shell age. Shell hardness was positively correlated with male size and peaked in stage 3 about 3.5 years after the terminal molt. The number of missing pereopods increased with shell age and SC stage and overall was negatively correlated with male size. The commercial value of adult males may be highest at 1‐4.5 years post‐terminal molt and the reproductive value at 2‐5.5 years.

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 score0.008
Threshold uncertainty score0.943

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 studies0.0000.003
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 head0.022
GPT teacher head0.232
Teacher spread0.210 · 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

Citations41
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueTransactions of the American Fisheries SocietySame topicCrustacean biology and ecologyFrench-language works237,207