Data from: Flow, flux and feeding in freshwater mussels
Bibliographic record
Abstract
Unionid mussels are important constituents of aquatic systems that are affected by anthropogenic changes in hydrology and concomitant increases in suspended solids, yet little is known about the effects of flow on their suspension feeding. We examined the clearance rates (CR) of four species of freshwater mussels (Lampsilis siliquoidea, Lampsilis fasciola, Ligumia nasuta and Villosa iris) to determine whether they feed selectively on river seston and how this may vary with algal flux (concentration × velocity). The CR for the Lampsilis species was also determined using seston particle size, particle fluorescence, and algal taxon. The CR of all species increased linearly with flow chamber velocity, but exhibited saturation-like kinetics with increasing algal flux. The CR of Lampsilis species were higher for larger (>10 um) vs. smaller (<10 um) particles, the latter of which were numerically dominant in river seston. The CR of Lampsilis mussels on most of the algal taxa declined (linearly or non-linearly) with algal flux indicating that mussels have reduced ability to discriminate among algae at higher flux. This potential feeding limitation could affect mussel growth and survival and make unionids vulnerable to the aforementioned hydrological changes. Ecologically, differential use of algal taxa under different algal flux indicates selective feeding, which may be evidence of resource partitioning for mussel species that occupy the same rivers. The differential use of algal taxa under different algal flux within a mussel species indicates the complex nature of bivalve feeding, their habitat requirements, and their vulnerability to human impacts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 0.002 |
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".