A large molluscivore bird (Common Eider, <i>Somateria</i><i> mollissima</i>) is able to discriminate quality of blue mussels (<i>Mytilus</i><i> edulis</i>) based on size and provenance
Bibliographic record
Abstract
Molluscivore birds that forage on abundant but low-quality food have to ingest large quantities of food to achieve energy balance. Such a strategy is often associated with important digestive constraints limiting predator’s ingestion. Thus, these predators may use prey selection to ingest better-quality individuals among a generally low-quality prey population. Using captive Common Eiders (Somateria mollissima (L., 1758)) diving in a constant environment, we were able to examine their preferences for blue mussels (Mytilus edulis L., 1758) of varying qualities (different sizes or provenances). In addition, we studied the consequences prey selection had on Eiders’ energy intake rates and ingestion of flesh and shell material. Eiders selected 10–20 mm mussels and were able to discriminate and to select cultivated mussels from intertidal mussels. Prey selection allowed, in certain conditions of prey-size abundance, higher flesh and energy intake rates without increasing the ingestion of shell material. This study confirmed the energetic advantage that Eiders have when foraging in aquaculture sites, which explain the large depredation of preferred mussel sizes.
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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) | 0.002 | 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".