Bibliographic record
Abstract
Peri-prosthetic distal femoral fractures around total knee replacement is a highly complex reconstructive challenge, particularly in the presence of bone comminution and poor bone quality in elderly patients. With the incidence of peri-prosthetic fractures ranging from 0.3% to 2.5%, this is becoming a common problem. Older patients with concomitant medical issues have a very limited tolerance for prolonged immobilisation. It is the author9s practice to revise, rather that attempt to fix, peri-prosthetic fractures of the knee which are very close to the femoral or tibial implants, particularly when associated with osteoporosis and comminution. When compared to fracture fixation, distal femoral replacement has significantly shorter operative time, less blood loss, and shorter hospital stay. Patients have been shown to recover faster, have fewer complications, and left hospital sooner. The general assumption has been that the use of a distal femoral replacement prosthesis is cost prohibitive in revision total knee settings, however, initial differences in the price of the prosthesis are more than offset by a shortened hospital stay and a more rapid return to pre-fracture level of function.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".