Effect of dietary phytic acid and semi-purified lignin on energy storage indices, growth performance, nutrient and energy partitioning of rainbow trout,<i>Oncorhynchus mykiss</i>
Bibliographic record
Abstract
The effect of dietary phytic acid (PA) and semi-purified lignin, and their interactions on growth performance, energy storage indices, nutrient deposition and partitioning in rainbow trout were studied in a 12-week growth trial. Six isoproteic and isoenergetic diets were formulated differing only in their PA and lignin concentrations. In these diets, five essential amino acids: histidine, lysine, methionine (+ cysteine), threonine and tryptophan were formulated to be marginally adequate to the dietary requirement. Fish were pair-fed with the amount of feed adjusted on a weekly basis. Among the performance indicators, dietary PA levels affected only the Fulton's body condition index (FCI) and whole carcass nitrogen retention efficiency (NRE; P < 0.05). On the contrary, lignin did not affect the whole carcass protein deposition (PD) and NRE but the lipid deposition (LD; P < 0.05), lipid retention efficiency (LRE; P < 0.01) and PD-LD ratio (P < 0.05). Neither lignin nor phytic acid affected any parameters in dressed carcass and in viscera of rainbow trout except the visceral LD, which was affected only by the PA-lignin interactions (P < 0.05).
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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 | 0.001 |
| 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".