Effects of hot-melt extruded nano-copper on the Cu bioavailability and growth of broiler chickens
Bibliographic record
Abstract
in nano or common forms. A total of 720 broiler chickens were distributed between eight treatments according to a completely randomized design. There were 8 treatments and 6 replicates in each treatment with 15 birds/replicate. The treatments were divided into common copper sulfate at the doses of 16 ppm, 40 ppm, 80 ppm, and 120 ppm (INO) and hot-melt extruded copper sulfate at the doses of 16 ppm, 40 ppm, 80 ppm, and 120 ppm (HME-Cu). The experiment was operated for 35 days in 2 phases (phase 1, d 0 to 14; and phase 2, d 15 to 35). No significant differences were shown in growth performance, feed intake, FCR, and nutrient digestibility among the treatments. The concentration of Cu in the serum was increased in the HME-Cu broilers compared with the INO broilers at phase 2. A linear increase was observed in the concentration of Cu in the liver in broilers fed INO diets, however, no significant differences were observed by the supplementation of HME-Cu levels. The linear increase was detected in the content of Cu in excreta in the INO and HME-Cu treatments by increasing the dietary Cu content. The HME-Cu treatments showed a lower Cu concentration in the excreta compared with the INO treatments. The higher bioavailability of Cu in HME form can decrease the recommended dose of Cu in broiler diets.
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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) | 0.001 | 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".