Bibliographic record
Abstract
This is the 2 nd issue of 2024.We are in the middle of the transition to quarterly publications and, yes, we do face adjustment issues.The most challenging one is not seeing the regular monthly issue, it is as simple as that!The 'due process' has not changed.All submitted papers are peer reviewed and the review process is more involved, detailed, and stricter.We have made this conscientious decision to improve the reputation of our journal, overcoming at the same time any 'open access' second thoughts.It is noted that, up to now, the number of submitted papers (in 2024) is less compared to previous years.However, we monitor the situation, and we do plan on bringing this issue to the Springer leadership and discuss it with them.I, as your Editor-in-Chief, correspond regularly with Ms. Nathalie Jacobs, who is also monitoring the situation.In any case, from our side nothing has changed.We continue doing a meticulous job, always looking for ways to be better and to better serve you.
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 | 0.013 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".