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Record W2066603734 · doi:10.1080/08927014.2014.953941

Byssus attachment strength of two mytilids in mono-specific and mixed-species mussel beds

2014· article· en· W2066603734 on OpenAlexaff
José M. F. Babarro, Luc A. Comeau

Bibliographic record

VenueBiofouling · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsByssusMytilusMusselAbiotic componentSalinityBlue musselBivalviaBiologyEcologyMollusca

Abstract

fetched live from OpenAlex

The mussel Xenostrobus securis is endemic to the brackish waters of New Zealand and Australia, but has successfully invaded the inner Galician Rías of NW Spain, where it coexists with the indigenous mussel Mytilus galloprovincialis. In this laboratory study, the plasticity of the byssus attachment strength of two mytilids was compared by manipulating substratum, salinity, and bed assembly. M. galloprovincialis showed stronger byssus detachment strength than X. securis, despite lower byssus coverage. Both species responded similarly to the substratum, with substantially lower byssus strength on methacrylate, which offered the lowest surface free energy. Byssus detachment values for M. galloprovincialis were lower at lower salinity. In mixed beds, a number of mussels moved upwards, eventually colonising the upper layers of the assemblage. This behaviour increased byssus strength but only for X. securis. X. securis is adapted to a wide spectrum of abiotic conditions, a trait that may promote its dissemination within estuarine environments.

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: Observational · Consensus signal: none
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 science0.0000.001
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 head0.018
GPT teacher head0.246
Teacher spread0.229 · 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

Citations17
Published2014
Admission routes1
Has abstractyes

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