Validation of a Novel Software Measurement Tool for Total Hip Arthroplasty
Bibliographic record
Abstract
) were compared with reference values using Student's t-test and chi-square test. Results For anteversion, mean values for the PRV (27.34° ± 7.27°) and the new software (27.29° ± 7.21°) were not significantly different (p = 0.49). The new software differed from the PRV by a mean of 0.05° ± 0.93°. Similar results were noted for inclination, where the new software differed from the PRV and SRV by -0.13° ± 0.65° and 0.25° ± 1.26°, respectively (mean values: PRV: 43.62° ± 6.02°; SRV: 43.99° ± 6.27°; new software: 43.74° ± 6.17°; p = 0.87), and for leg length, where the new software differed from the PRV and SRV by 0.05 mm ± 0.46 mm and 0.22 mm ± 0.52 mm, respectively (mean values: PRV: 10.61 mm ± 11.60 mm; SRV: 10.77 mm ± 11.70 mm; new software: 10.56 mm - ± 11.61 mm; p = 0.98). Measurements were highly correlated across multiple reviewers (intraclass correlation coefficient ≥0.987). Conclusions The new software measurement tool is accurate and precise for assessing the acetabular component position and leg length measurements following THA in AP pelvic radiographs compared to currently used image measurement software.
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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 | 0.017 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".