Bibliographic record
Abstract
Scientific research is disseminated within the community and to the public in part through journals. Most scientific journals, in turn, protect the manuscript through copyright and recover their costs by charging subscription fees to individuals and institutions. This revenue stream is used to support the management of the journal and, in some cases, professional activities of the sponsoring society such as the Institute of Electrical and Electronics Engineers (IEEE). For example, the IEEE Engineering in Medicine and Biology Society (EMBS) manages seven academic publications representing the various areas of biomedical engineering. New business models have been proposed to distribute journal articles free of charge, either immediately or after a delay, to enable a greater dissemination of knowledge to both the public and the scientific community. However, publication costs must be recovered and likely at a higher cost to the manuscript authors. While there is little doubt that the foundations of scientific publication will change, the specifics and implications of an open source framework must be discussed.
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 | 0.021 | 0.177 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.022 | 0.012 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.408 | 0.265 |
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".