Fitness-to-work considerations in the paradigmatic pain condition of headache disorder
Bibliographic record
Abstract
Headache disorders are common, including in the working population. Clinicians caring for patients with headache need to be aware of work-related factors as potential causes or triggers of headache disorders, and consider the impact of headache on fitness-to-work, especially in safety-sensitive and decision-critical roles. Such fitness-to-work determination should include individualized consideration of the nature of the headache disorder itself, the pattern of the headache, the impact of sleep deprivation on the headache as it relates to fitness to do shiftwork, medication and substance side effects, fitness-to-work implications of associated medical or psychiatric conditions, and the potential of symptom feigning or malingering for secondary gain. As clinicians often struggle with fitness-to-work determinations, a structured approach to fitness-to-work assessments in headache conditions and other pain conditions would improve clarity for clinicians and increase the quality of care provided to patients, with potential benefits for workplace safety and policy in this arena as well.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".