Inter-surgeon variability in the identification of clock face landmarks when placing suture anchors in arthroscopic Bankart repair
Bibliographic record
Abstract
BACKGROUND: The accuracy of surgeons in utilizing the clock face method for anchor placement has never been investigated. Our hypothesis was that shoulder arthroscopy surgeons would be able to place suture anchors at predetermined positions with accuracy and reliability. METHODS: Ten cadaveric shoulders were used. Five fellowship-trained shoulder arthroscopy surgeons were directed to place a suture anchor at 3:30, 4:30, and 5:30 clock in two shoulders each. The position of the anchors was determined with computed tomography. The accuracy of placement was calculated and data analyzed with one-way analysis of variance. The intraclass correlation coefficients were calculated. RESULTS: The overall accuracy was 57%. The accuracy of anchor placement at the 3:30 position was 40% (average position 2:24 o'clock), it was 50% at the 4:30 position (average position 3:42 o'clock) and 80% at the 5:30 position (average position 5:03 o'clock). No statistical difference in accuracy between the placement of the superior, middle, and inferior anchors (p = 0.145) was seen. The intraclass correlation coefficient for inter-surgeon reliability was 0.4 (fair) while the intraclass correlation coefficient for intra-surgeon reliability was 0.6 (moderate). DISCUSSION: The findings of this study suggest a moderate degree of accuracy and fair to moderate inter- and intra-surgeon reliability when using the clock face system to guide anchor placement.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".