Quantification of<i>in vivo</i>implant wear in total knee replacement from dynamic single plane radiography
Bibliographic record
Abstract
An in vivo method to measure wear in total knee replacements was developed using dynamic single-plane fluoroscopy. A dynamic, anthropomorphic total knee replacement phantom with interchangeable, custom-fabricated components of known wear volume was created, and dynamic imaging was performed. For each frame of the fluoroscopy data, the relative location of the femoral and tibial components were determined, and the apparent intersection of the femoral component with the tibial insert was used to calculate wear volume, wear depth, and frequency of intersection. No difference was found between the measured and true wear volumes. The precision of the measurements was ±39.7 mm(3) for volume and ±0.126 mm for wear depth. The results suggest the system is capable of tracking wear volume changes across multiple time points in patients. As a dynamic technique, this method can provide both kinematic and wear measurements that may be useful for evaluating new implant designs for total knee replacements.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".