The Bone and Joint Decade 2000–2010 Task Force on Neck Pain and Its Associated Disorders
Bibliographic record
Abstract
Scott Haldeman, DC, MD, PhD,1 Linda Carroll, PhD,2 J. David Cassidy, DC, PhD, DrMedSc,3 Jon Schubert, CMA,4 and Ake Nygren, DDS, MD, DrMedSc5 1Department of Neurology, University of California, Irvine, CA; Department of Epidemiology, School of Public Health, University of California, Los Angeles, CA 2Department of Public Health Sciences, and Alberta Center for Injury Control and Research, School of Public Health, University of Alberta, Canada 3Department of Public Health Sciences, Faculty of Medicine, University of Toronto an Division of Health Outcomes and Research, Toronto Western Research Institute, University Health Network, Toronto, Canada 4CEO–SGI, Regina, Saskatchewan, Canada 5Department of Clinical Sciences, Danderyd Hospital, Division of Rehabilitation Medicine, Karolinska Institutet, Stockholm, Sweden
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".