Bibliographic record
Abstract
Purpose: The purpose of this study was to investigate the characteristics of patients with Chronic Low Back Pain (CLBP) in disability, pain, and cognition, and to compare those characteristics to the ICF concept analyzing the association between World Health Organization Disability Assessment Schedule 2.0: 12 item-interviewer version (WHODAS 2.0) and those of scales i.e. Oswestry Disability Index (ODI), the Short-Form McGill Pain Questionnaire (SFMPQ), and the Fear avoidance & belief questionnaire (FABQ). Methods: A total of 91 patients with CLBP were invited to participate in the study. Physical therapists interviewed all participants using SFMPQ, FABQ, ODI, and WHODAS 2.0 for collection of information on pain, cognition, and functional level data. Subjects scored their disability, pain, and cognition related to LBP using WHODAS 2.0, ODI, SFMPQ, and FABQ. Data analysis was performed using the Spearman correlation coefficient. Results: A positive relationship was observed between WHODAS 2.0 and each scale indicating that lower back specific disability components could be related to the ICF concept in ODI (r=0.77). Pain intensity and pain oriented movement were found to be related to general functioning in patients with CLBP (r=0.52, r=0.55, respectively). Conclusion: It can be suggested that the specific disability scale for LBP, ODI can be related to the ICF concept, WHODAS 2.0, and it may be a useful measure for patients with CLBP.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".