PERAN PENYULUH DALAM PEMBELAJARAN INSEMINASI BUATAN KEPADA PETERNAK SAPI DI KECAMATAN KAWANGKOAN BARAT KABUPATEN MINAHASA
Bibliographic record
Abstract
ROLE OF INSTRUCTOR ON ARTIFICIAL INSEMINATION LESSON TO CATTLE FARMERS IN WEST KAWANGKOAN DISTRICT MINAHASA REGENCY. The purpose of this study was to examine how the role of instructors in learning artificial insemination to cattle farmers in West Kawangkoan District, Minahasa Regency, that is by looking at the role of extension agents, the success of IB learning and the role of extension agents with the success of artificial insemination learning to cattle farmers. Data collection was carried out by direct interviews with cattle breeders assisted by questionnaires. Data analysis using index percent formula for determining variable values and simple correlation analysis to see the relationship between the role of instructor variables and the success of artificial insemination learning to cattle farmers. The results of the analysis show that the role of the instructor is in good category and the success of learning artificial insemination is in the successful category, so there is a relationship between the role of instructor and the success of artificial insemination learning to cattle farmers in West Kawangkoan District, Minahasa Regency.Keywords: Role of instructor, learning of artificial insemination, cattle ranchers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".