Exercise for Prevention of Recurrences of Nonspecific Low Back Pain
Bibliographic record
Abstract
Low back pain (LBP) is highly prevalent2 and a common reason for presentation to primary care. 3 The direct and indirect costs associated with this condition are enormous and represent a significant economic burden to health care systems. The prognosis of those with acute LBP is generally positive, with approximately 72% recovering by 1 year. 4 For those who recover, recurrences within the next 12 months following recovery are common. 5,6 It has been well-established that nonspecific LBP is often recurrent and that 24% to 87% of those who recover from an episode of LBP will have a recurrence within 1 year. 5‐8 A theme that is current among clinicians and researchers is the difficulty in defining a recurrence of LBP. Various clinicians and researchers
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".