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Record W2117004143 · doi:10.1093/plankt/fbv059

Pelagic population dynamics of<i>Aurelia</i>sp. in French Mediterranean lagoons

2015· article· en· W2117004143 on OpenAlexaff
Raquel Marques, Séverine Albouy‐Boyer, Floriane Delpy, Claire Carré, Emilie Le Floc’h, Cécile Roques, Juan-Carlos Molinero, Delphine Bonnet

Bibliographic record

VenueJournal of Plankton Research · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine Invertebrate Physiology and Ecology
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsPelagic zoneMediterranean climateZooplanktonWater columnBiologyOceanographyAbundance (ecology)Mediterranean seaEcologyVoltinismPopulationBloomGeology

Abstract

fetched live from OpenAlex

The pelagic dynamics of the cosmopolitan scyphozoan Aurelia sp. was investigated in three French Mediterranean lagoons, Thau, Berre and Bages-Sigean, which harbour resident populations. The annual cycles showed a common univoltine pattern in all lagoons where the presence of pelagic stages in the water column lasted ∼8 months. Field observations showed a release of ephyrae in winter time followed by pronounced growth between April and July, when individuals reached the largest sizes, before disappearing from the water column. Maximum abundance of ephyrae and medusae were registered in Thau. Medusae abundance attained a maximum of 331 ind 100 m−3 in Thau, 18 ind 100 m−3 in Berre and 7 ind 100 m−3 in Bages-Sigean lagoons. Temperature and zooplankton abundance appeared as leading factors of growth, where Bages-Sigean showed the population with higher growth rates (2.66 mm day−1) and maximum size (32 cm), followed by Thau (0.57–2.56 mm day−1; 22.4 cm) and Berre (1.57–2.22 mm day−1; 17 cm). The quantification of environmental windows used by the species showed wider ranges than previously reported in the Mediterranean Sea, which suggests a wide ecological plasticity of Aurelia spp. populations in north-western Mediterranean lagoons.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.086
GPT teacher head0.328
Teacher spread0.242 · 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 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

Citations33
Published2015
Admission routes1
Has abstractyes

Explore more

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