Bibliographic record
Abstract
Links between the regulation of sleep and pediatric pain are complex and bi-directional: pain may disrupt sleep (Palermo, 2000) and, in turn, sleep loss may enhance pain sensitivity (see Lewin & Dahl, 1999 for a conceptual review). Research has demonstrated far-reaching consequences of sleep disruptions in healthy children including increased school absences and academic and attentional difficulties (Fallone et al., 2002; Wolfson & Carskadon, 1998). In adolescents with chronic pain, disturbed sleep has been associated with significant impairments in a broad range of physical and social activities along with reductions in overall health-related quality of life (Palermo & Kiska, 2005). In this commentary, we review the literature in this area organized by the primary method of sleep assessment: subjective self-report, polysomnography, and actigraphy. Due to the paucity of literature, we consider chronic pain conditions together, recognizing that future research may demonstrate differences in the nature and role of sleep disturbance as a function of the type of chronic pain problem.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".