Bibliographic record
Abstract
1. Keinginan untuk anak-anak. 2. Putra atau putri. 3. Kesuburan wanita. Kematian bayi. 4. Pengadaan aborsi. 5. Pembuahan. Siapa yang menjalani konsekrasi. 6. Impregnasi yang tidak normal. 7. Kemandulan. 8. Kehamilan tidak normal. 9. Kehamilan normal. 10. Larangan selama kehamilan. 11. Persalinan. 12. Bidan. 13. Persalinan yang tertunda. 14. Posisi-posisi anak dilahirkan. Posisi kepala. 15. Posisi kaki. 16. Terlahir dengan caul. 17. Anak tidak menangis saat lahir. 18. Keguguran dan kembar. 19. Lahir mati. Anak-anak yang meninggal segera setelah lahir. 20. Tembuni (towuni). 21. Perawatan bayi baru lahir. 22. Perawatan wanita dalam persalinan. 23. Larangan bagi wanita dalam persalinan. 24. Kematian wanita dalam waktu bersalin. 25. Mengunjungi wanita dalam waktu bersalin. 26. Menyusui. 27. Mengurangi dan meningkatkan aliran air susu ibu. 28. Anak disusui oleh wanita lain. 29. Menyapih anak.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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; both teacher heads agree on what is shown here.
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".