Comportamiento productivo y características físicas de huevo producido por gallinas criollas Copetonas y Marans
Bibliographic record
Abstract
Objective: The present study was conducted to evaluate the productive performance and egg physical characteristics of two backyard-type breeds of birds. Design/methodology/approach: Tufted Creole Hens (TCH; 13 hens and a rooster) and Marans (13 hens and a rooster), were used in this study. Live body weight, feed intake, egg production, egg weight, egg length and egg width were measured weekly during eight weeks. Collected data were analyzed using a two-way analysis of variance, the main factors were breed, week and their interaction. Results: Marans hens were heavier and had higher feed intake than the TCH (P<0.05). The egg of the TCH was smaller (P <0.05) in weight and length with respect to that of Marans hens. TCH produced more eggs than the Marans hens (P <0.05). The week factor was significant (P <0.05) for body weight, feed intake and egg length. Limitations on study/implications: Further studies should be carried out to design a feeding program that would allow both breeds to express their full productive potential and maximize the return on investment in backyard production systems in Mexico. Findings/conclusions: Marans hens are a heavier breed due to their greater live body weight and feed intake with respect to TCH. The TCH are lighter birds but with a higher egg production when compared to the Marans.
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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 | 0.001 | 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".