A comprehensive evaluation of <i>Daphnia pulex</i> foraging energetics and the influence of spatially heterogeneous food
Bibliographic record
Abstract
Aquatic organisms are distributed in a heterogeneous, nonrandom manner, and zooplankton are known to seek out and orient themselves within regions of high food concentration. Yet, the energetics associated with this foraging behavior are unknown. We hypothesized that zooplankton foraging behavior increases foraging efficiency measured as food consumption per unit effort. In this study, we measured the energetic costs and benefits for the zooplankton Daphnia pulex foraging in a range of algal concentrations to determine the net energetic benefit of foraging in algal patches. The net energy benefit of foraging increased significantly with increases in algal concentration; this trend was driven by significant increases in prey ingestion with algal concentration, whereas foraging costs did not change. Even considering corrections for changes in assimilation efficiency, foraging in algal patches greatly increases net foraging benefit compared to foraging in low concentrations of algae and thus has the potential for higher reproduction and greater growth in filter-feeding zooplankton.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".