Assessment of egg quality parameters in Himsamridhi chicken variety under intensive housing in Himachal Pradesh
Bibliographic record
Abstract
The present study was carried on Himsamridhi chicken variety to assess the effect of age on egg quality traits. A total of 300 eggs were collected for studying the external and internal egg quality parameters at different age groups i.e. 24, 30, 36, 44 and 50 weeks. Most of the egg quality traits differed (P<0.05) significantly at different age of measurements. Egg weight increased as the age of bird advanced and varied from 40.35±0.89 g at 24 week of age to 51.85±0.64 g at 50 week of age. Length, width and height of albumen increases as the age of bird progresses. Albumin index was found to be significantly (P<0.05) higher at 24 weeks of age. The yolk index found to be significantly (P<0.05) higher at 36 week of age. Albumen and yolk percentage varied from 57.76 to 60.01 % and 29.87 to 31.95 % respectively at different ages of measurements. Haugh unit index was observed to be significantly higher at 24 weeks of age and ranged from 82.93 to 88.78 indicating uniform internal egg quality over the age. Correlation coefficient of egg weight with egg length, egg width, albumen length, albumen width and yolk width were positive. Shell percentage and Haugh unit was negatively correlated with egg weight at 30, 44 and 50 weeks of age. The result reveals significant variation in egg quality parameters with different age of measurements.
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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".