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Record W6884542244 · doi:10.1051/alr/2011115/pdf

Biochemical and genetic characteristics of suspension-cultured mussels (

2011· article· en· W6884542244 on OpenAlexfundaboutno aff

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsnot available
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsByssusMytilusMusselThread (computing)Blue musselBiofouling

Abstract

fetched live from OpenAlex

Mussel culture relies on the mussel self-attachment capacity through byssus production. By doing so, no cages or containment devices are needed. It has been previously suggested that thread production requires a non-negligible part of the energy expenditure in blue mussels Mytilus edulis. Therefore our work investigates the relationships between byssal thread production, mussels energetic reserves and phospholipids profiles in the foot. The relationship between thread production and heterozygosity was also examined. The study was realized in a small lagoon of the Îles-de-la-Madeleine, southern Gulf of St. Lawrence, Canada, on four sampling dates between June and September encompassing the pre- to post-spawning periods. Our results show a significant relationship between the thread numbers and attachment strength. However, no correlations were found between energy reserves, phospholipids composition of the foot or heterozygosity level and byssal production. Our results suggest that mussels in suspension culture in this lagoon were not energy-limited so that the energy reserves did not influence the byssal thread production.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.013
GPT teacher head0.217
Teacher spread0.203 · 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 designBench or experimental
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

Citations0
Published2011
Admission routes2
Has abstractyes

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