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SEDIMENT SELECTION BY JUVENILE SEA SCALLOPS (CANCER IRRORATUS SAY)

2006· article· en· W2103719339 on OpenAlexaff
Melisa C. Wong, Lisa Wright, Myriam A. Barbeau

Bibliographic record

VenueJournal of Shellfish Research · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsScallopBiologyAsteriasFisheryBiological dispersalPredationArgopecten irradiansEcologyStarfishPopulation

Abstract

fetched live from OpenAlex

We examined sediment selection by juvenile sea scallops (Placopecten magellanicus) and their predators, sea stars (Asterias vulgaris) and rock crabs (Cancer irroratus). In laboratory trials, groups of scallops (~30 mm shell height) were simultaneously offered four sediment types in the presence and absence of a sea star or a rock crab: (1) glass representing a homogeneous, hard bottom; (2) sand; (3) granule and (4) pebble. As well, individual predators were offered the four sediment types without scallops. The number of scallops and the proportion of time predators spent on each sediment type were monitored over time. When compared with the expected distribution, scallops avoided glass and tended to select granule and pebble sediments when alone. In the presence of a rock crab, scallops also avoided glass. However, scallop distribution was similar to the expected distribution when a sea star was present, because sea star encounters are an important trigger of scallop swimming, leading to frequent redistribution of scallops. Sea stars spent less time than expected on glass, whereas crabs spent more time than expected on sand. For both predators, distribution did not change significantly in the presence or absence of scallops. In sum, scallop distribution appears more dependent on predator distribution than the reverse. Predation of scallops by sea stars and rock crabs was not influenced by sediment type. Our results have implications for the bottom culture of scallops. Because scallops select heterogeneous sediments over homogeneous ones, dispersal of scallops may be important on unsuitable sediments. Also, dispersal may be higher when sea stars are present at an aquaculture site.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0250.000

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 head0.025
GPT teacher head0.318
Teacher spread0.293 · 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.

Study designNot applicable
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
Published2006
Admission routes1
Has abstractyes

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