Computer-assisted femoral head resurfacing
Bibliographic record
Abstract
Femoral head resurfacing is re-emerging as a surgical option for younger patients who are not yet candidates for total hip replacement. However, this procedure is more difficult than total hip replacement, and the mechanical jigs typically used to align the implant produce significant variability in implant placement and take a significant amount of time to position properly. We propose that a computer-assisted surgical (CAS) technique could reduce implant variability with little or no increase in operative time. We describe a new CAS technique for this procedure and demonstrate in a cadaver study of five paired femurs that the CAS technique in the hands of a novice surgeon markedly reduced the varus/valgus variability of the implant relative to the pre-operative plan (2° standard deviation for CAS versus 5° for a mechanical jig operated by an expert surgeon). We also show that the mechanical jig resulted in significantly retroverted implant placement. There was no significant difference in operative time between the two techniques.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".