Bibliographic record
Abstract
The system of Arabic transliteration used in this work follows that of the Institute of Islamic Studies, McGill University.Indonesian terms arc written according to the E}"aan Baru Bahasa Indonesia (I 972), except personal names and titles of books or articles, which arc rendered according to the original spellings (see below).Likewise, all Arabic words that have been adopted into Indonesian will be written according to Indonesian spelling, without indicating their Arabic diacritical signs, such as Muhammadiyah, instead of Afulzammadrvah; Majlis Tarjih, instead of i\!fajlis al-Tarjz/.z,and al-lrsyad instead of al-Irshad.However, the ta' marbutah (~) is transliterated as "ah" form, and "at'' in conjunction form; such as al-'ibadah and al-/zanifz_yat a!-samfzah.Indonesian words indicating personal names or titles of books and articles that originate from the works before the 1972 Indonesian spelling system will be retained as they are.The main difference between the old and new Indonesian spelling systems can be seen as listed below:
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.044 | 0.038 |
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".