Bibliographic record
Abstract
The circadian rhythm disorder often known as shift work sleep disorder (SWSD) is characterized by the presence of insomnia symptoms and/or sleepiness occurring in relation to a work schedule. According to epidemiological studies, 14%–32% of night workers and 8%–26% of rotated night workers suffer from SWSD. This sleep disorder is explained by the fact that shift workers are sleeping during the day when their biological clock is normally facilitating wakefulness. Therefore, there is a circadian misalignment between wake and sleep periods. In addition to this biological explanation, several psychosocial factors have been linked to SWSD and hypothesized as having an influence on the adaptation capacities to shift work. Psychological factors such as depression or sociological factors such as marital satisfaction are presented in an integrative model to give a broader view of the course of SWSD. Actual recommended assessment and treatment options followed by behavioral treatment suggestions are presented thereafter. The authors hope that the innovative conceptualization of SWSD presented within this chapter will bring attention to different relevant topics for future research in order to improve the clinical management of SWSD in the long term.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.036 | 0.024 |
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".