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Record W2888343922 · doi:10.1051/alr/2018007

Temporal variation of secondary migrations potential: concept of temporal windows in four commercial bivalve species

2018· article· en· W2888343922 on OpenAlexafffund
Martin Forêt, Réjean Tremblay, Urs Neumeier, Frédéric Olivier

Bibliographic record

VenueAquatic Living Resources · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsUniversité du Québec à Rimouski
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsBiological dispersalRuditapesPecten maximusMytilusBenthic zoneInterspecific competitionHabitatOceanographyEcologyIntertidal zoneBivalviaEnvironmental scienceMolluscaBiologyFisheryGeologyPopulation

Abstract

fetched live from OpenAlex

Post-settlement dispersal potential of four commercial bivalve species ( Mytilus edulis , Pecten maximus , Venus verrucosa and Ruditapes philippinarum ) were studied through the assessment of recruits' sinking velocities by using a sinking velocity tube of five meters height. In parallel, dynamics of shear stress were monitored for five months on a tidal habitat characterized by the presence and the dispersal of the four species. By coupling both datasets we propose first theoretical estimates of temporal windows of secondary migrations. These experiments revealed interspecific differences in migration potential relate to shell shapes and behaviour, especially to secretion of byssal threads. The sensitivity to passive and active post-settlement migrations seems to rely on the synchronisation between the arrival on the sediment, the tidal regime (spring tide, neap tide), but also the rate of growth of the recruits. The present study confirms that patterns of secondary migrations of bivalve recruits result from a close physical-biological coupling involving benthic boundary layer (BBL) hydrodynamics and shell morphology as well as eco-ethological responses to environmental conditions but clearly modulated by the growth dynamics until a threshold size when drifting is no longer possible.

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)0.001
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.014
GPT teacher head0.234
Teacher spread0.221 · 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

Citations8
Published2018
Admission routes2
Has abstractyes

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