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Record W3201467724 · doi:10.1111/ivb.12346

Population structure, habitat preferences, feeding strategies, and diet of the brittle star <scp><i>Ophiopholis aculeata</i></scp> in nearshore and offshore habitats of the northwest Atlantic

2021· article· en· W3201467724 on OpenAlexafffundabout
Fanny Volage, Jean‐François Hamel, Annie Mercier

Bibliographic record

VenueInvertebrate Biology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEchinoderm biology and ecology
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsBiologyHabitatEcologyPredationIntraspecific competitionPopulationCompetition (biology)

Abstract

fetched live from OpenAlex

Abstract Ophiopholis aculeata is a ubiquitous brittle star (Echinodermata: Ophiuroidea) known to occur from the upper subtidal to the bathyal zone. Individuals from shallow inshore habitats (rhodolith beds and rock fields) and deeper offshore locations in eastern Canada were studied to assess the population structure, habitat selection, diet, and feeding strategies of this species through use of stable isotope analyses, gut contents, and laboratory experiments. Potential drivers of habitat selection such as depth, light conditions, body size, sex, intraspecific competition, and presence of predators were examined. This study highlighted variable population size structures and abundances as well as diversified food sources and feeding strategies (i.e., suspension and deposit feeding, scavenging, predation on live organisms, and even cannibalism) as a function of native depth and habitat. It also revealed that studies on the feeding biology of brittle stars must carefully consider sex and life stage as driving factors.

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 score0.025
Threshold uncertainty score0.050

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 head0.017
GPT teacher head0.212
Teacher spread0.195 · 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
Published2021
Admission routes3
Has abstractyes

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