Bibliographic record
Abstract
Open access (OA) has been gaining momentum in the world of scholarly publication for the past 15 years. An article published with the OA model is freely accessible to the public—i.e., it does not sit behind a publisher’s “pay wall.” This movement has been fueled in large part by governmental funders of research who believe that the published product of their support should be available without charge to the entire research community and to the public who provided the funding. To cover the costs of the editorial/peer-review process in the OA model, authors (or their institution) pay an article processing charge (APC), averaging $2,000 to $5,000. This fee is often included in federal or foundation grants that authors receive to conduct their research. After a lengthy period of discussion by the JBJS Editorial Board and Board of Trustees, we are pleased to announce the launch of JBJS Open Access. This new, online-only journal will expand our ability to publish basic-science and clinical findings as well as new research approaches that have the potential of impacting musculoskeletal disease and injury care worldwide. We believe that this journal option will be of greatest interest to authors from non-North American regions, where the OA funding mandate is quite strong. JBJS Open Access manuscripts will undergo the same rigorous peer review for which JBJS is known. This will be overseen by newly appointed Co-editors Dr. Eng Lee from Singapore and Dr. Robin Richards from Canada, both highly experienced basic and clinical science investigators who possess over 60 years of combined experience in scholarly publication activities. In addition, all accepted papers will undergo the same extensive copy-editing process that is provided for all JBJS publications. The APC for publication in JBJS Open Access has been set at $2,250. This fee will be collected after acceptance and will have no influence on the editorial decision-making process for a manuscript. JBJS is excited to be able to offer JBJS Open Access as one more step in our continuing effort to meet our authors’ and readers’ evolving needs. We are proud that authors will now have an OA publication option while receiving the outstanding services and brand of excellence that JBJS has been providing its authors for over 125 years—and that a wider audience of readers will have access to the best in orthopaedic information.
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 | 0.030 | 0.178 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.026 | 0.013 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.019 | 0.023 |
| Insufficient payload (model declined to judge) | 0.378 | 0.243 |
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".