Reliability of Centroid, Cobb, and Harrison Posterior Tangent Methods
Bibliographic record
Abstract
STUDY DESIGN: Thirty lateral thoracic radiographs were digitized twice by each of the three examiners. OBJECTIVES: To determine the reliability of the centroid, Cobb, and Harrison posterior tangent methods when applied to analysis of thoracic kyphosis. BACKGROUND DATA: Reliability studies on measurements of thoracic kyphosis are rare. METHODS: Blind, repeated-measures design was used. Thirty lateral thoracic radiographs were digitized twice by each of three examiners. To evaluate reliability of determining global and segmental alignment, vertebral bodies of T1-T12 were digitized. Centroids at the intersection of vertebral body diagonals and tangents to posterior vertebral bodies were constructed by computer. Also the computer constructed global and segmental centroid angles, Cobb angles (two-line method), and posterior tangent intersection angles from T1 to T12. Interclass and Intraclass correlation coefficients for these data were calculated and interpreted. RESULTS: From the points selected by examiners, all three methods have similar high ICC values for the global angles (> 0.94). For the segmental angles, the interobserver and intraobserver reliability is also very similar for all three methods, with ICCs in the good and excellent ranges (0.59-0.75 and 0.75-1.0, respectively). The mean absolute differences of observers' measurements are low, similar, and in the range of 0.9 degrees to 2.5 degrees. CONCLUSIONS: The centroid, two-line Cobb, and Harrison posterior tangent methods, when applied to measurements of kyphosis, are all reliable and have similar small error ranges. The centroid method does not give an accurate segmental analysis, uses more points and more time in clinical applications, and results in smaller angles of total kyphosis than the Cobb or posterior tangent methods. The posterior tangents are the slopes along the curve.
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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 | 0.025 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".