Bibliographic record
Abstract
To the Editor: We thank Dr. Kapur for the comments1 on our recent editorial2. Many patients who have minor injuries in motor vehicle accidents can progress to develop significant and persistent pain. Often these patients fulfill criteria for fibromyalgia (FM), which is the most common chronic pain phenotype3. The presence of psychological distress occurring in this context is the key to subsequent development of chronic musculoskeletal pain4,5. In these situations, it is important to “get the diagnosis right” because FM is associated with central pain while whiplash implies ongoing peripheral nociceptive pain. The term “whiplash” is an emotive term because it implies that the neck has been forcefully traumatized by the motor vehicle accident, thus implying ongoing injury. The term “fibromyalgia” is descriptive and defined by robust clinical criteria3,6. The central pain of FM has its origins in changes in control … Address correspondence to Dr. Littlejohn, Suite H, Monash Medical Centre, 246 Clayton Road, Clayton, Victoria, Australia. E-mail: Geoff.littlejohn{at}monash.edu
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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 | 0.004 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.036 | 0.036 |
| Insufficient payload (model declined to judge) | 0.008 | 0.007 |
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".