Inter- and Intra-observer Agreement of the Motion Palpation Test for Lumbar Vertebral Rotational Asymmetry
Bibliographic record
Abstract
PURPOSE: To investigate inter- and intra-observer agreement in the assessment of lumbar vertebral rotational (VR) asymmetry by a motion palpation test. METHODS: For this prospective and descriptive test-retest study, 51 asymptomatic participants (40 women, 11 men; mean age 23.3 [SD 5.6] years) were recruited from the community. Each participant was assessed in two sessions by the same three observers, who assessed VR by means of a palpatory test for movement asymmetry. This test is performed by applying posteroanterior pressure in an alternating manner to the left and right transverse processes of a vertebra to determine motion asymmetry in the transverse plane and thus the vertebral position. Observers classified the vertebral position as neutral, rotation to the right, and rotation to the left; they were blinded to which participant was being assessed and to any previous results. RESULTS: Intra- and inter-observer agreement was verified by the kappa coefficient (κ) and the weighted kappa coefficient (κ w ). Values of κ and κ w varied from 0.07 (95% CI, -0.10 to 0.245) to 0.37 (95% CI, 0.11-0.63) for intra-observer agreement and from 0.12 (95% CI, -0.06 to 0.29) to 0.30 (95% CI, 0.08-0.52) for inter-observer agreement. CONCLUSION: The motion palpation test used to assess VR asymmetry has low agreement levels; therefore, its clinical significance for measuring vertebral position is questionable.
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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 | 0.038 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".