Type III functional response in the zebra mussel, <i>Dreissena polymorpha</i>
Bibliographic record
Abstract
Distinguishing between functional response types requires observations at low food concentrations, but surprisingly these tend to be rare. A paucity of feeding observations at low food concentrations is especially acute for dreissenid mussels, despite their importance as invading species in fresh waters. We assessed the functional response of zebra mussels (Dreissena polymorpha) via feeding experiments and behavioral observations conducted at low food levels. Critically, food levels were chosen to be in the vicinity of minimum concentrations found in lakes with established D. polymorpha populations. Results of two feeding experiments show clear evidence of a Type III functional response for D. polymorpha feeding on Ankistrodesmus falcatus — clearance rate increased with increasing food concentration at low food levels. Mussels were always open and feeding during these experiments. An independent set of behavioral observations further showed that the fraction of mussels actively feeding (valves open, siphons extended) decreased as food concentrations decreased. We also measured somatic growth of juvenile mussels at varying levels of A. falcatus over 27 days and found that mussels were able to grow at food levels where Type III behavior was observed in the feeding experiments.
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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".