Understanding the patellofemoral joint in total knee arthroplasty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Total knee arthroplasty (TKA) is one of the most successful procedures in orthopedic surgery. Nevertheless, postoperative patellofemoral complications remain a challenging problem, affecting a substantial proportion of patients. Complications involving the patellofemoral joint (PFJ) can occur in both resurfaced and nonresurfaced patellae. Types of PFJ complications include anterior knee pain, maltracking, fracture, avascular necrosis and patellar clunk. The causes of patellofemoral complications can be categorized into patient-, surgeon- and implant-related factors. Patient characteristics such as female sex, young age, depression and increased body mass index have been linked with increased complications. Important technical considerations to avoid complications include achieving appropriate rotational alignment of the femoral and tibial components, maintaining joint line height, medializing the patellar button and avoiding “overstuffing” the PFJ. Component design features such as conformity, shape and depth of the femoral trochlea have also been shown to be important. Although the cause of patellofemoral complications after TKA may sometimes be unknown, it remains important to minimize errors that can lead to these complications.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it