Disturbances in sleep, circadian rhythms and daytime functioning in relation to coronavirus infection and Long‐COVID – A multinational ICOSS study
Bibliographic record
Abstract
Summary This protocol paper describes the second survey produced by the International Covid Sleep Study (ICOSS) group with the aim to examine the associations between SARS‐CoV‐2 infection and sleep, sleepiness, and circadian problems as potential predisposing factors for more severe COVID‐19 disease profile and for development of Long‐COVID in the general population. The survey consists of 47 questions on sleep, daytime sleepiness, circadian rhythm, health, mental wellbeing, life habits, and socioeconomic situation before and during the pandemic, and conditional questions to those reporting having had coronavirus infection, being vaccinated, or suffering from particular sleep symptoms or sleep disorders. Surveys will be administered online between May and November 2021 in Austria, Brazil, Bulgaria, Canada, China, Croatia, Finland, France, Germany, Israel, Italy, Japan, Norway, Portugal, Sweden and USA. Data collected by the survey will give valuable information on the open questions regarding COVID‐19 disease risk factors, symptomatology and evolution of Long‐COVID, and on other long‐term consequences related to the pandemic.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".