Attachment of zebra and quagga mussel adhesive plaques to diverse substrates
Bibliographic record
Abstract
Like marine mussels, freshwater zebra and quagga mussels adhere via the byssus, a proteinaceous attachment apparatus. Attachment to various surfaces allows these invasive mussels to rapidly spread, however the adhesion mechanism is not fully understood. While marine mussel adhesion mechanics has been studied at the individual byssal-strand level, freshwater mussel adhesion has only been characterized through whole-mussel detachment, without direct interspecies comparisons on different substrates. Here, adhesive strength of individual quagga and zebra mussel byssal plaques were measured on smooth substrates with varying hydrophobicity-glass, PVC, and PDMS. With increased hydrophobicity of substrates, adhesive failures occurred more frequently, and mussel adhesion strength decreased. A new failure mode termed 'footprint failure' was identified, where failure appeared to be adhesive macroscopically, but a microscopic residue remained on the surface. Zebra mussels adhered stronger and more frequently on PDMS than quagga mussels. While their adhesion strengths were similar on PVC, there were differences in the failure mode and the plaque-substrate interface ultrastructure. Comparisons with previous marine mussel studies demonstrated that freshwater mussels adhere with comparable strength despite known differences in protein composition. An improved understanding of freshwater mussel adhesion mechanics may help explain spreading dynamics and will be important in developing effective antifouling surfaces.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".