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Record W2010646813 · doi:10.1017/s0025315400002198

Field examination of dispersion patterns of juvenile Iceland scallops (<i>Chlamys islandica</i>) in the northern Gulf of St Lawrence

2000· article· en· W2010646813 on OpenAlexaff
David J. Arsenault, Martin C. Giasson, John H. Himmelman

Bibliographic record

VenueJournal of the Marine Biological Association of the United Kingdom · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsUniversité LavalBamfield Marine Sciences Centre
Fundersnot available
KeywordsScallopJuvenileOceanographyBivalviaMolluscaFisheryGeologyBiologyEcologyPaleontology

Abstract

fetched live from OpenAlex

The movement of juvenile Iceland scallops, Chlamys islandica , was quantified in an inshore bed in the Mingan Islands, northern Gulf of St Lawrence, to examine whether the size partitioning over depth in this location, increasing scallop size with depth, results from a gradual downslope movement as scallops increase in size. Scallops of 30.0-44.9 mm and 45.0-59.9 mm in shell height were collected using SCUBA, tagged, and released in the centre of two 0.4-km 2 grids at 15 m in depth. After 7 d and 48 d, the net distance moved by the scallops from the release points did not vary between the two size groups but varied significantly between grids. The majority of scallops (70-94%) moved downslope and the mean movement vectors were not orientated in the direction of tidal currents, but rather towards increasing depth. The downslope movement of the scallops was possibly explained by more prolonged swimming bouts when scallops swam downslope. The results suggest that the spatial size partitioning of Iceland scallops at this location is caused by a gradual downslope movement as the scallops increase in size. This study provides the first experimental evidence supporting the controversial hypothesis of recruitment into adult scallop populations involving swimming of juveniles from nursery areas.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.789

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.227
Teacher spread0.213 · 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

Citations13
Published2000
Admission routes1
Has abstractyes

Explore more

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