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Comparative analysis of Byssal thread production, mechanical properties, and composition in diploid and triploid Mytilus edulis

2025· article· en· W4416768391 on OpenAlexafffund
Kevin Osterheld, John Davidson, Luc A. Comeau, Tiago S. Hori, José M. F. Babarro, Isabelle Marcotte, Alexandre A. Arnold, Christian Pellerin, Richard Saint‐Louis, Réjean Tremblay

Bibliographic record

VenueAquaculture · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsUniversité de MontréalUniversité du Québec à MontréalFisheries and Oceans CanadaUniversité du Québec à Rimouski
FundersFonds de recherche du Québec – Nature et technologiesFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMytilusByssusMusselMolluscaBivalviaJuvenile

Abstract

fetched live from OpenAlex

Mussel fall-off continues to pose a major challenge for suspension-culture farming, leading to substantial crop losses. Although studies on juvenile mussels (<30 mm) have indicated that triploids may exhibit enhanced byssal thread attachment and reduced fall-off, their performance in adult mussels remains insufficiently explored. In this study, we investigated the production, mechanical strength, biochemical composition, and structural features of byssal threads in diploid and triploid mussels of commercial size (>50 mm). We also calculated metabolic and filtration rates, as well as scope for growth. Our results revealed that triploid mussels produced 25 % more byssal threads with significantly enhanced mechanical properties. Triploid mussels conditioned at 20 °C exhibited a 48 % higher clearance rate, a 57 % greater scope for growth, and a 40 % stronger valve (breaking strength) compared to diploids. These findings suggest that triploid mussels over 50 mm have superior attachment strength relative to wild mussels, primarily due to increased 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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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