Feeding Traits and Body Dimensions of Lime and Parkote Buffaloes Raised by Small-Scale Farms in Kaski, Nepal
Bibliographic record
Abstract
Thirty farms that raised Lime or Parkote female buffaloes in Kaski were selected for the survey of animal census, feeding traits and body dimensions in the rainy season and the dry season. The average number per farm was 0.76 in Lime and 0.27 in Parkote. The average of age and parity was 8.2 years old and 4.4 in Lime, and 6.6 years old and 2.8 in Parkote, respectively. The mean dry matter (DM) supply of roughage, supplemental feed and total feed was higher in the dry season than in the rainy season (11.8 kg/head/day vs. 10.3 kg/head/day, 1.2 kg/head/day vs. 0.8 kg/head/day, 13.0 kg/head/day vs. 11.1 kg/head/day, respectively, P<0.05). Although the average DM supply of roughage per body weight (BW) and total feed supply per BW had no significant differences between the seasons, the mean DM supply of supplemental feed per BW was higher in the dry season than in the rainy season (0.35% of BW vs. 0.22% of BW, P<0.01). The BW, heart girth (HG) and hip born width (HW) of Parkote were higher than those of Lime (401.7 kg vs. 368.0 kg, 185.7 cm vs. 179.8 cm, 50.4 cm vs. 48.4 cm, respectively, P<0.05). However, the body length, wither height (WH) and criss-cross height showed no significant differences between Lime and Parkote (127.4 cm and 129.8 cm, 118.7 cm and 119.5 cm, 118.0 cm and 119.4 cm, respectively). The BW estimation using body dimensions may play a significant role to know about the buffalo body condition. With the measured BW, HG, WH and HW in this survey, the formulae to estimate BW of Lime and Parkote buffaloes were established.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".