Bibliographic record
Abstract
The best papers presented at the 2012 Basic Science Focus Forum are included in this issue of the Journal of Orthopedic Trauma. The papers at the meeting were graded by the Basic Science Focus Forum program committee, and those selected and published in this supplement were found to be of the highest quality. We have included highly relevant review articles on hot topics related to the biomechanics of fracture fixation, atypical femur fractures, and thromboembolic disease. These reviews will be extremely relevant to practicing clinicians and give them information that will be immediately applicable to their own practices. There is also a significant focus on fracture repair, stem cell biology, and infection in this issue. In particular, there currently exists a real interest in cell-based therapies for fracture and nonunion repair, and as such, we have included timely and relevant articles devoted to endothelial progenitor cells and mesenchymal stem cells. The information presented herein provides state of the art information for those attempting to remain current with the explosion of information in the field of fracture and nonunion repair, particularly as it relates to cell-based therapies. We hope that this issue of the Journal of Orthopedic Trauma will once again continue to stimulate readers to substantially contribute to the Basic Science Focus Forum in future years and make further contributions to our understanding of fracture and nonunion repair.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.309 | 0.198 |
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; the direct Gemma label and the distilled Codex classifier 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".