Interactions between food quantity and quality (long-chain polyunsaturated fatty acid concentrations) effects on growth and development of<i>Chironomus riparius</i>
Bibliographic record
Abstract
We quantified somatic growth, development, and emergence of the midge Chironomus riparius on experimental diets (oats, Spirulina, and Tetraphyll®) covering gradients in food quality (differing polyunsaturated fatty acids) and quantity (0.1–5.4 mg C·day–1). Additionally, similar incubations without food additions were made using a food-poor sediment containing peat and the green alga Scenedesmus obliquus. Larval and adult size was affected by both food quantity and quality and increased some three to four times across the food concentration gradients. Adult emergence, however, was affected only by food quantity. A type 3 response model showed that a saturation level was reached for the oats treatment at 2.7 mg C·day–1(or 3.9 µg ω3 and 120 µg ω6 polyunsaturated fatty acids·day–1), indicating that the quality of oats constrained further stimulation of larval growth. In the peat treatment, larval growth was very low, no adults emerged, and no larvae even made it to the pupa stage. Fatty acid analyses showed that larvae were capable of synthesizing arachidonic acid via γ-linolenic acid by Δ6- and Δ5-desaturase activity using linoleic acid available in food sources. This strongly suggests that C. riparius is not dependent on dietary sources of eicosapentaenoic acid and arachidonic acid and can sustain viable populations even under a low-quality food regimen.
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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 | 0.001 |
| 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".