Bibliographic record
Abstract
The rapid growth of Canadian pork industry has been challenged by its negative impact on the environment. To find an economical and promising solution to the environmental problems, 4% zeolite (90%+ clinoptilolite) were supplemented to a regular (100% crude protein (CP) and energy) or low CP and energy (90% CP and 90% energy or 90% CP and 85% energy) grower pig diets. Twenty male and twenty-four female grower pigs were used in two feeding experiments respectively, followed by a metabolic test with three batches of animals repeated to determine the metabolic effects of zeolite supplementation. Pig performance (body weight gain, daily feed intake and feed conversion ratio), and metabolic parameters (manure mass, feed intake, protein and energy conversion, as well as dry feed and organic matter retention) were evaluated. Zeolite supplementation at 4% to a regular diet for grower pigs had a positive but not significant (P > 0.05) effect on all pig performance and metabolic parameters, compared to the regular diet without zeolite. Among 4 rations, pigs on a regular diet with 4% zeolite performed consistently best throughout the entire trail, with decreased average daily consumption and reduced amount of feces, increased feed and organic matter retention in the gastrointestinal tract, improved feed as well as protein and energy conversion, and enhanced body weight gain. Moreover, zeolite supplementation at 4%, with 90% CP and 90% energy in grower pig diets, improved feed and protein and energy conversion rate, and increased body weight gain, when compared to those of pigs fed a regular diet without zeolite. However, a diet of 90% of CP and 85% of energy with 4% zeolite significantly (P < 0.05) increased feed consumption and the amount of feces produced, and decreased feed and organic matter retention in the gastrointestinal tract, thus reducing feed conversion rate. Therefore, 4% zeolite supplementation to the regular or low CP and energy (90% C Key words. Clinoptilolite, Pig, Pig Performance, Metabolic Parameter.
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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".