HUBUNGAN RIWAYAT PAPARAN PESTISIDA DENGAN KEJADIAN GOITER PADA ANAK SEKOLAH DASAR DI WILAYAH KERJA PUSKESMAS KLUWUT KECAMATAN BULAKAMBA KABUPATEN BREBES
Bibliographic record
Abstract
Tingginya penggunaan pestisida dapat menyebabkan pencemaran lingkungan, keracunan dan terakumulasi pada produk pertanian, sehingga berdampak buruk terhadap kesehatan.Pestisida menyerang sistem saraf, hati, perut, sistem kekebalan dan keseimbangan hormonal.Kabupaten Brebes sebagai produsen bawang merah terbesar di Indonesia terdapat ± 700 merk pestisida dan merupakan daerah endemis GAKI.Prevalensi goiter tertinggi di Wilayah Kerja Puskesmas Kluwut, sebesar 107 anak positif goiter (68,6%).Tujuan penelitian untuk mengetahui hubungan antara riwayat paparan pestisida dengan kejadian goiter pada anak sekolah dasar di Wilayah Kerja Puskesmas Kluwut Kecamatan Bulakamba Kabupaten Brebes.Jenis penelitian adalah observasional analitik dengan rancangan studi kasus kontrol.Teknik sampling menggunakan metode random sampling dengan 45 kasus dan 45 kontrol.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 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".