PERBEDAAN KADAR KOLINESTERASE ANTARA PEMAKAI INSEKTISIDA PADA PETANI PALAWIJA DENGAN PEMAKAI HERBISIDA PADA PETANI PENANAM KOPI REJANG LEBONG, CURUP, BENGKULU
Bibliographic record
Abstract
Tujuan penelitian ini adalah untuk mengetahui adanya perbedaan kadar kolineterase antara pemakai insektisida pada petani palawija di Desa Sember Urip Kecamatan Selupu Rajang dengan pemakai herbisida pada petani penanam kopi di desa Tunas Harapan Kecamatan Curup Kabupaten Rejang Lebong Curup Bengkulu. \n \nPenelitian ini adalah penelitian explanatory dengan metode survei danpendekatan cross sectional. Populasi penelitian adalah semua petani yang ada di Desa Sumber Urip dan Desa Tunas Harapan. Sample ditentukan secara purposive sample dengan criteria: Janis kelamin laki-laki, kontak terakhir dengan pestisida masksimal 2 minggu, menyemprot dengan pestisida golongan organofospat dan karbamat. Status kesehatan, responden tidak sedanga menderita penyakit hepatitis, abses dan kanker hati. Didaptakn sample sebanyak 26 petani. \n \nDari hasil penelitian diperoleh: tidak ada perbedaan antara responden yang terpapar insektisida dengan responden yang terpapar herbisida (t hitung \n \n \n \nKata Kunci: insektisida, herbisida, dan kolinesterase
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.005 |
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".