Faktor Risiko Potensial Reaksi Kusta Pada Etnis Asli di Dua Kantong Kusta – Papua
Bibliographic record
Abstract
Abstract Papua and West Papua are two provinces in Indonesia with high rate of leprosy number. One of the problems in leprosy management is the emergence of leprosy reactions. The purpose of this study was to identified potential risk factors affecting to leprosy reaction among indigenous people in two leprosy pockets in Papua and West Papua. Cross-sectional studies were conducted in 10 months (February-November 2018) in Jayapura City and Bintuni District, by interview using questionnaire and physical examination. Successfully found 90 subjects of leprosy patients who are undergoing treatment and 18 subjects had experienced of leprosy reaction. Although no dominant potential risk factor was found, history of previous MDT consumption and history of BCG immunization become potential factors. Key words: reaction, leprosy, papua Abstrak Papua dan Papua Barat merupakan dua provinsi di Indonesia dengan angka kejadian kusta yang tinggi. Salah satu masalah dalam penanganan kusta adalah timbulnya reaksi kusta. Tujuan dari penelitian ini untuk mengidentifikasi faktor risiko potensial yang berpengaruh pada reaksi kusta pada etnis asli di dua kantong kusta di Papua dan Papua Barat. Penelitian potong lintang dilakukan selama 10 bulan (Februari-November 2018) di Kota Jayapura dan Bintuni, menggunakan wawancara dengan kuisioner dan pemeriksaan fisik. Berhasil ditemukan 90 subyek pasien kusta yang sedang menjalani pengobatan dan 18 di antaranya pernah mengalami reaksi kusta. Meskipun tidak ditemukan faktor risiko potensial yang dominan, namun riwayat minum MDT sebelumnya dan riwayat tidak diimunisasi BCG menjadi faktor-faktor yang potensial. Kata kunci: reaksi, kusta, papua
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".