Bibliographic record
Abstract
As we move into the New Year 2018, JGH Open will change to a bi-monthly schedule starting from February. I hope by doing this, we will be able to consolidate the journal by having more articles per issue. I am happy to confirm that article processing charges will be waived for the whole of 2018. Meanwhile, applications will be made to Pub Med Central and the Emerging Sources Citation Index (ESCI) in the first quarter of 2018. These will be our first steps in the long journey to gain ISI citation. The JGH Open has been pleased to accept several cascaded articles from the JGH but we look forward to more direct submissions from researchers and clinicians across the Asian Pacific region and throughout the world. In 2018 we will strive to have more leading articles, every issue, written by eminent key opinion leaders from the region. I hope these articles, which will be on cutting-edge and/or pertinent topics to our clinical and scientific practice, will prove attractive to our readers.
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 | 0.005 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.012 | 0.019 |
| Insufficient payload (model declined to judge) | 0.021 | 0.021 |
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".