Insights into the feeding of jellyfish polyps in wild and laboratory conditions: do experiments provide realistic estimates of natural functional rates?
Bibliographic record
Abstract
Abstract Biotic and abiotic factors that affect the physiology and ecology of scyphozoan polyps are considered to be major drivers of jellyfish blooms, but are rarely studied under field conditions. Here, stable isotopes of carbon and nitrogen were used to investigate feeding ecology in Aurelia aurita polyps from the Beaulieu River, UK (50° 80′ 04.55″ N/1° 42′ 28.12″ W) in both winter and summer conditions, and compared to laboratory-maintained polyps fed Artemia nauplii at 6 and 20 °C, respectively. In natural conditions, the isotopic composition of A. aurita polyps indicated assimilation of nutrients derived from both benthic and pelagic food pathways, with seasonal switches between benthic-derived nutrients in winter and pelagic-derived nutrients in summer. In laboratory experiments, polyps assimilated Artemia food at 6 °C although metabolic processes were reduced, while at 20 °C, polyps starved as their increased metabolic costs could not be met from the Artemia food. Experiments on growth and asexual reproduction of Artemia -fed polyps of A. aurita may not reflect natural metabolic rates especially at higher temperatures (e.g. 20 °C), because these polyps are not extracting sufficient resources from their Artemia food to fuel the increased metabolic costs associated with high temperatures.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".