Computer-Assisted Correction of Cam-Type Femoroacetabular Impingement
Bibliographic record
Abstract
BACKGROUND: Assessing the adequacy of bone resection when correcting cam-type femoroacetabular impingement can be difficult when the surgeon is inexperienced or when less-invasive arthroscopic surgical techniques are used. The primary purpose of the present study was to compare, using a Sawbones model, the results of computer-assisted navigated osteochondroplasty of the femoral neck junction with correction with use of femoral head spherometer gauges. The second objective was to compare the results of computer-assisted osteochondroplasty performed by surgeons who had varied experience with the procedure. METHODS: We calculated and compared the post-resection alpha angle in custom-molded Sawbones models with cam-type impingement following both surgical techniques, performed by three surgeons with varied experience with the procedure. The alpha angle was measured at two positions (the three o'clock and one-thirty positions of the femoral head-neck junction) before and after resection. RESULTS: At the three o'clock position, there were no significant differences between the computer-navigation and spherometer groups (p = 0.83). There was undercorrection at the one-thirty position, with the median alpha angle being greater in the navigation group as compared with the spherometer group (71.0 compared with 58.6; p = 0.05). In the navigation group, there were no significant differences in the post-resection mean alpha angle among the three surgeons at either the one-thirty plane or the three o'clock plane. CONCLUSIONS: Navigation enabled the inexperienced surgeon to perform an equivalent amount of bone resection as the more experienced surgeons. However, all surgeons did not sufficiently resect the cam deformity as compared with the gold-standard open technique at the one-thirty position.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".