Substratum patch selection in the lacustrine mussels <i>Elliptio complanata</i> and <i>Pyganodon grandis grandis</i>
Bibliographic record
Abstract
1. Sediment selection was investigated under controlled conditions in two common lake‐dwelling species of freshwater mussels (Bivalvia: Unionidae), Elliptio complanata and Pyganodon grandis grandis. 2. Sediment choice was determined in six independent experiments under controlled conditions by distributing mussels randomly or evenly in tanks containing patches of sand and mud, and following their movement among sediment patches in experiments lasting between 30 and 45 days. 3. In all experiments, both species were found most frequently in muddy sediment patches. Movement toward muddy patches occurred rapidly: an average of nearly 80% of Pyganodon grandis grandis were found in mud after 30 days. Elliptio complanata moved rapidly to patches of mud at the start of experiments, but occupation of muddy sediments appeared to decrease after about 30 days. 4. Our results contrast with many field studies that suggest populations of lake‐dwelling freshwater mussels infrequently inhabit mud and silt. We therefore postulate that large‐scale mussel distribution in lakes is influenced most strongly by factors other than sediment composition.
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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".