KID CROP DAN MORTALITAS ANAK KAMBING KACANG DI DAERAH DARATAN DAN KEPULAUAN KABUPATEN BUTON
Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengetahui produktivitas ternak Kambing Kacang berdasarkan nilai kid crop dan mortalitas anak Kambing Kacang baik di wilayah kepulauan maupun wilayah daratan Kabupaten Buton. Penelitian ini dilaksanakan di Kecamatan Siompu (mewakili wilayah kepulauan) dan di Kecamatan Lapandewa (mewakili wilayah daratan) Kabupaten Buton. Metode penentuan lokasi penelitian dilakukan secara purposive sampling, stratified sampling dan simple random sampling dan penentuan responden di setiap desa dilakukan secara sensus. Data penelitian dianalisis secara deskriptif. Hasil penelitian menunjukkan bahwa kid crop Kambing Kacang di Kecamatan Siompu sebesar 150,98% dan Kecamatan Lapandewa sebesar 159,84%. Kidding Interval Kambing Kacang di Kecamatan Siompu sebesar 8,2 bulan dan di Kecamatan Lapandewa sebesar 8,19 bulan. Di Kecamatan Siompu diperoleh rataan litter size sebesar 1,77 dan di Kecamatan Lapandewa sebesar 1,53. Jumlah cempe Kambing Kacang yang lahir di Kecamatan Siompu sebanyak 84 ekor (38 ekor jantan dan 46 ekor betina). Di Kecamatan Lapandewa jumlah cempe Kambing Kacang yang lahir sebanyak 68 ekor (37 ekor jantan dan 31 ekor betina). Persentase mortalitas cempe kambing Kacang di Kecamatan Siompu sebesar 22,61% dan di Kecamatan Lapandewa sebesar 11,76%. Dapat disimpulkan bahwa produktivitas dan reprodutivitas ternak Kambing Kacang baik di wilayah kepulauan maupun di wilayah daratan Kabupaten Buton masih sangat baik, namun, tingkat mortalitas cempe di wilayah kepulauan masih relatif tinggi.Kata Kunci: Kambing Kacang, Performans, Kid Crop, Mortalitas, Lapandewa, Siompu
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".