MétaCan
Menu
Back to cohort
Record W3195089561 · doi:10.1371/journal.pone.0256369

A small step or a giant leap: Accounting for settlement delay and dispersal in restoration planning

2021· article· en· W3195089561 on OpenAlexaboutno aff
Ana Rodríguez‐Pérez, Mark James, William Sanderson

Bibliographic record

VenuePLoS ONE · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsnot available
FundersScottish Funding CouncilMarine Alliance for Science and Technology for ScotlandHeriot-Watt University
KeywordsMetamorphosisBiological dispersalLarvaBiologyContext (archaeology)Ostrea edulisOysterFisheryPelagic zoneEcologyPopulationDemographyPaleontology

Abstract

fetched live from OpenAlex

Understanding larval duration and hence dispersal potential of the European oyster Ostrea edulis is crucial to inform restoration strategies. Laval duration has an obligatory period of maturity to pediveliger (when larvae are ready to settle), but also an unknown period until metamorphosis is triggered by a settlement cue. The extent to which larvae can prolong the pediveliger period and delay metamorphosis has not been studied. Here we show that O. edulis larvae can delay metamorphosis for a period of 11 days, while retaining the capability to settle in high proportions when presented with a suitable settlement cue. O. edulis larvae are likely to be able to delay metamorphosis even further, since 80% of larvae in the control treatment were still alive when the experiment was terminated at day 14. The results indicate the ability of O. edulis larvae to more than double pelagic duration and probably further delay metamorphosis. We discuss these findings in the context of larval mortality, and the importance of O. edulis' larval settlement requirements for dispersal potential, recruitment success and connectivity of restoration sites.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.062
GPT teacher head0.259
Teacher spread0.197 · 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 designSimulation or modeling
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

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuePLoS ONESame topicMarine Bivalve and Aquaculture StudiesFrench-language works237,207