Reliability of Lower Limb Frontal Plane Alignment Measurements Using Plain Radiographs and Digitized Images
Bibliographic record
Abstract
This study evaluated the reliability of lower limb frontal plane alignment measures obtained from plain radiographs measured manually and digitized images measured using a custom computer software package (TheHTO Pro; Fowler Kennedy Sport Medicine Clinic, London, Ontario, Canada). Radiographic measurements used in the planning of high tibial osteotomy, including the mechanical axis angle and mechanical axis deviation, were measured on 42 hip-to-ankle radiographs on two separate occasions by two different raters (A.V.S., J.J.D.). Intraclass correlation coefficients (0.96-0.99) indicated excellent agreement between the manual and computer measurements, suggesting both methods can be used interchangeably. Although test-retest and inter-rater reliability tended to be slightly better when using TheHTO Pro, intraclass correlation coefficients were excellent for both methods (0.97-0.99). The standard errors of measurement were <1 degree for mechanical axis angle and <2 mm for mechanical axis deviation, regardless of method or rater. Based on the observed standard errors of measurement, conservative estimates for the error associated with an individual's mechanical axis angle at one point is approximately 1.5 degrees, and the minimal detectable change on reassessment is approximately 2 degrees. The error associated with an individual's mechanical axis deviation at one point is approximately 4 mm, and the minimal detectable change on reassessment is approximately 6 mm. These results suggest that manual and computer measurements of lower limb frontal plane alignment can be calculated with minimal measurement error. However, the small errors associated with both methods should be considered when making clinical decisions.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".