Total replacement of maize with raw or heat-treated sweet cassava tuber meal on productive performance and egg quality parameters in Jumbo quail hens from 6 to 14 weeks of age
Bibliographic record
Abstract
The impact of complete replacement of maize with raw or heat-treated sweet cassava ( Manihot esculenta) tuber meal (CTM) on productive performance and egg quality of Jumbo quail hens was determined. A total of 240, 6-week-old hens were randomly allocated to 60 cages (4 birds/cage) and assigned to five experimental diets with 12 replicates each. The diets were a standard layer mash diet without CTM (CON) and a standard layer mash diet in which 100% maize was replaced with raw (CTMR), boiled (CTMB), autoclaved (CTMA), and oven-dried CTM (CTMO). The highest overall feed intake, body weight gain, and final body weight ( P < 0.05) was observed from the CON group while the lowest was from the CTMB group. Overall FCR and mortality were not significantly influenced by the diets. Fourteen-week-old hens on CON had a higher ( P < 0.05) rate of lay than CTMR. Eggs from CON had the brightest yolk colour values than all the treatment groups. Moreover, eggs from CON had the least shape index than those from CTMO. Diet CTMA promoted heavier ( P < 0.05) eggshells than CTMR. Jumbo quail hens reared on maize-based diet showed better performance followed by autoclaving treatment, whereas boiling treatment compromised performance traits.
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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".