Chronic low-back pain: intercorrelation of repeated measures for pain and disability
Bibliographic record
Abstract
Subjective experience of pain and disability was assessed for 4-5 weeks on a weekly basis in 14 consecutive out-patients complaining of low-back pain and/or leg pain that had lasted for at least 6 months. The following measures were used for assessment: a visual analogue scale (VAS) (present pain and worst pain during preceding 2 weeks), a short-form McGill Pain Questionnaire (SF-MPQ), the Pain Disability Index (PDI) and the pain drawing. In addition, psychological variables of pain experience were evaluated with the Comprehensible Psychopathological Rating Scale (CPRS). When the median of the variation coefficient for repeated measures was compared, the most stable measures were, in rank order: PDI, total number of words chosen in the SF-MPQ and worst pain during the preceding two weeks (VAS). The Spearman correlation showed statistically significant intercorrelation for present pain assessed with the VAS score, for the sensory word score of the SF-MPQ and for the PDI. Especially the PDI, which represents a global score for disability, showed very little test-retest variability and a high intercorrelation with the other methods of assessment, i.e. the pain drawing, the VAS scale for pain and the SF-MPQ.(ABSTRACT TRUNCATED AT 250 WORDS)
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".