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Record W1870526181 · doi:10.1651/s-2771.1

Individual Identification of Decapod Crustaceans II: Natural and Genetic Markers in Snow Crab (Chionoecetes Opilio)

2007· article· en· W1870526181 on OpenAlexafffund
Thierry Gosselin, Bernard Sainte‐Marie, Jean‐Marie Sévigny

Bibliographic record

VenueJournal of Crustacean Biology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsUniversité du Québec à RimouskiFisheries and Oceans Canada
FundersNatural Sciences and Engineering Research Council of CanadaAdobe Systems
KeywordsBiologyCrustaceanCarapaceIdentification (biology)MatingZoologyMoultingSnowDecapodaEcologyMicrosatelliteNatural (archaeology)FisheryGeneGenetics

Abstract

fetched live from OpenAlex

Methods for the identification of individual crustaceans are needed in many types of studies. Snow crab (Chionoecetes opilio) individuals have distinctive natural patterns of tubercles and spines on the carapace. The results of a double-marking experiment using these natural markers along with genetic (microsatellite) markers confirm that natural markings are a reliable means of recognizing individuals within groups of tens to hundreds of snow crabs. These natural markings are persistent through at least two molts. They have already demonstrated their usefulness in laboratory studies of molting and mating and could be applied to a wider spectrum of investigations. A cursory examination suggests that similar carapace features could be used to identify individuals in other crustacean species as well.

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 score0.002
Threshold uncertainty score0.003

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)0.0010.000

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 head0.009
GPT teacher head0.251
Teacher spread0.242 · 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

Citations14
Published2007
Admission routes2
Has abstractyes

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