Bibliographic record
Abstract
Usaha peternakan memberi kontribusi terhadap penyediaan produksi ternak, peningkatan pendapatan peternak, perluasan dan penciptaan lapangan kerja.�?� Pengembangan usaha peternakan dengan pola kemitraan PIR antara industri peternakan (perusahaan) sebagai inti dengan peternak sebagai plasma merupakan bentuk kerjasama yang saling menguntungkan dan mempercepat pencapaian target pembangunan sub sektor peternakan yang merupakan bagian dari tujuan pengembangan wilayah. Tulisan ini menyajikan kontribusi usaha peternakan dengan pola kemitraan PIR dalam pengembangan wilayah. Berdasarkan hasil suatu penelitian tentang peranan usaha peternakan dengan pola kemitraan PIR ayam ras pedaging dalam pengembangan wilayah di Kabupaten Deli Serdang menunjukkan bahwa indeks LQ (Location Quotient) > 1 yang berarti bahwa eksistensi usaha peternakan termasuk kegiatan usaha berbasis di dalam peningkatan pendapatan (Produk Domestik Regional Bruto) di wilayah Provinsi Sumatera Utara. Dengan demikian usaha peternakan dengan pola kemitraan PIR di Kabupaten Deli Serdang menjadi andalan dalam pembangunan wilayah.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.048 | 0.018 |
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".