The digestive and metabolic enzyme activity profiles of a nonmetamorphic marine fish species: effects of feed type and feeding level
Bibliographic record
Abstract
We investigated activity levels of metabolic and digestive enzymes in Atlantic wolffish (Anarhichas lupus) and their relationships with growth, ration level, and type of food during the first 50 days after hatch. Newly hatched wolffish were divided among three experimental groups differing in feed and ration (formulated feed in excess (FF), a maintenance ration of Artemia (LA), and Artemia in excess (EA)) that generated different growth rates. A principal component analysis revealed that activities of the glycolytic enzymes lactate dehydrogenase (LDH) and pyruvate kinase (PK) were associated with mass gain, while those of the aerobic enzymes citrate synthase and aspartate aminotransferase (AAT), and digestive enzymes (lipase and trypsin) were related to time (days) after hatch. Food restriction or food type allowed the observation of a direct relationship between the activities of trypsin and those of associated metabolic enzymes AAT and glutamate dehydrogenase in the LA group (Pearson's R of 0.71 and 0.59, respectively), as well as between the activities of amylase and those of LDH and PK (Pearson's R of 0.62 and 0.48, respectively) in the FF group. The adaptative importance of these patterns during early development of wolffish and their relationship to feeding conditions are examined.
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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".