Bibliographic record
Abstract
1. Bumi dan surga terletak di atas satu sama lain. 2. Tangga antara langit dan bumi. 3. Jalan lain menuju surga. 4. Liana sebagai jalan menuju surga. 5. Bumi tergantung di langit. 6. Asal muasal gempa bumi. 7. Takut gempa. 8. Pelangi. 9. Pelangi meramalkan kematian. 10. Dasar pelangi. 11. Pelangi sebagai pertanda jahat. 12. Menunjuk pelangi. 13. Tanda-tanda akan turunnya hujan dan kekeringan. 14. Meminta hujan dan kekeringan. 15. Cara menarik dan menghentikan hujan. 16. Takut akan hujan. 17. Asal usul badai. 18. Cara menghentikan badai. 19. Asal usul guntur dan kilat. 20. Takut pada guntur. 21. Matahari dan lintasannya. 22. Asal usul matahari. 23. Pernikahan matahari dan bulan. 24. Kunjungan ke matahari. 25. Gerhana Matahari. 26. Matahari dalam kehidupan sehari-hari. 27. Lingkaran mengelilingi matahari. 28. Bulan. 29. Bulan dan pertanian. 30. Pohon beringin di bulan. 31. Tanda-tanda di bulan. 32. Nama-nama bintang. 33. Rasi bintang "Ayam jantan". 34. Bintang adalah manusia. 35. Penentuan waktu berdasarkan bintang. 36. Venus. 37. Bima Sakti. 38. Komet. 39. Alasan ada manusia yang tinggal di bulan. Babi dengan kuku emas. (Direkam di Gintu, Bada' in Lore). 40. Pria yang menikah dengan gadis bulan. 41. Adik bulan. 42. Gadis yang mengawini bulan. 43. Pohon beringin di bulan. 44. Putri Salju Bada. 45. Mitos bulan Napu. 46. Rasi bintang "Ayam jantan". 47. Kisah lain tentang konstelasi "Ayam jantan". 48. Bacaan lain dari konstelasi “Ayam”. 49. Rasi bintang "Ayam" diasosiasikan dengan ratu asli dan ratu palsu". 50. Ringkasan beberapa mitos dari Bada'. 51. Kisah Tonili (direkam di Rondingo di Pakawa). 51a. Kisah Toilu dan Ntiwolu di Rampi. 52. Kisah Tololopalo "titik pantat". 53. Kisah Kolombio (direkam di Rondigo di Pakawa). 54. Cerita lain dari Kolombio (direkam di Pakawa). 55. Kisah Tonda Labua dan Sanggilana. 56. Mitos bulan kelompok Sigi. 57. Kisah Woo dodo. 58. Varian dari cerita sebelumnya. 59. Mitos bulan yang berkaitan dengan asal usul beras.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.237 | 0.151 |
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".