Inter-rater reliability of the Active Straight-Leg Raise and One-Leg Standing tests in non-pregnant women
Bibliographic record
Abstract
OBJECTIVE: To determine the inter-rater reliability of the Active Straight-Leg Raise and One-Leg Standing tests. DESIGN: Cross-sectional pilot study. SUBJECTS: Thirty-one women who were either not pregnant or at least 9 months post-partum. METHODS: Subjects completed a questionnaire and standardized pain and disability assessments. The Active Straight-Leg Raise and One-Leg Standing tests were assessed by 3 independent, blinded examiners. Inter-rater reliability was determined, and relationships with assessments were explored. RESULTS: For the Active Straight-Leg Raise test, the kappa coefficient was 0.87, sensitivity 71%, and specificity 91%. Relationships with various pain and disability assessments were demonstrated, including the Functional Pelvic Pain Scale (r = 0.77) and Roland-Morris Disability Questionnaire (r = 0.70). For the One-Leg Standing test, kappa coefficients were -0.02 and 0.14 for the left and right sides, respectively, and thus no further analyses were performed. CONCLUSION: In women with a spectrum of low-back and pelvic pain, the Active Straight-Leg Raise test had good inter-rater reliability, whereas the One-Leg Standing test did not. Further studies are required regarding the validity of the Active Straight-Leg Raise test.
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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 | 0.033 | 0.083 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".