POTENSI PENGEMBANGAN TERNAK SAPI POTONG DENGAN POLA INTEGRASI KELAPA-SAPI DI KECAMATAN TABARU KABUPATEN HALMAHERA BARAT
Bibliographic record
Abstract
This study aims to (1) Analyzing Potential of Beef Cattle Development with Pattern of Integration of Coconuts in Tabaru Subdistrict of West Halmahera Regency (2) fresh forage production coconut plant area in Tabaru Subdistrict of West Halmahera Regency (3) the nutrional content of forage the coconut plant area in Tabaru Subdistrict of West Halmahera Regency (4) potential population of cattle and animal unit (AU) in Tabaru Subdistrict of West Halmahera Regency (5) revenue through integration and non integration in Tabaru Subdistrict of West Halmahera Regency. The research was conducted in Tabaru district of West Halmahera district since Desember 2017 to February 2018. The determination of respondents was performed using simple random sampling method. Criteria of respondents involved in this study were household farmers running a coco-beef integration, at least animal maintenance of more than one year and they had sold cattle. The results showed the particular characteristics of household farmers including coconut plantation ownership of 3.8 ha with the average number of animals of 10.2 heads, the average education level of primary school, the animal breeding experience of 12,7 years and animal maintenance purposes as beef production and animal labor. Management aspects of farm animals were still under the traditional maintenance systems, animals were resistant to disease, and house hold farmer knowledge on animal reproduction was still limited. Aspects of feed resources were positively supporting in the development of beef cattle under integration pattern, especially the nutritional value of forage and land carrying capacities and Livestock productivity aspects had quite well potential.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".