Bibliographic record
Abstract
Treatment of periprosthetic femur fracture is based on fracture timing, implant stability, fracture pattern, and bone quality. Intraoperative fractures are usually stable; to prevent intraoperative fracture, careful preoperative planning and gentle operative techniques are essential. In managing unstable intraoperative and late postoperative periprosthetic fractures, the surgeon should be know the exact pattern of fracture, prosthesis stability, and bone quality. Loose prostheses should be revised and displaced fractures should be reduced and adequately fixed. These fractures typically occur in the peritrochanteric area, and their treatment is cerclage wiring or cables. Postoperative periprosthetic fractures are usually the result of trauma in the setting of loosening of the prosthesis and/or osteolysis. Periprosthetic femoral fractures are classified using the Vancouver classification, which is based on the location of the fracture, the amount of available proximal bone stock, and the stability of the stem. Correct classification of these fractures is important, as it helps to guide treatment.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".