Synergistic effect of social media use and psychological distress on depression in China during the <scp>COVID</scp>‐19 epidemic
Bibliographic record
Abstract
psychosis. 4 Psychosis post-NIH1-virus infection in children was associated with viral-induced brain-reactive autoantibodies production. 5 Severance et al. 6 found a higher level of immunoglobulin G against four different human coronavirus strains in adults diagnosed with psychosis versus controls. An interesting aspect of the case reported is the concomitant occurrence of the psychotic episode and the pulmonary thromboembolism, as both thrombotic phenomena and neuropsychiatric symptoms have been recently described as potential sequelae of the inflammatory storm and the immunoreactivity associated with COVID-19. 7, 8 The hypothesis of the occurrence of psychosis as an adverse reaction to some of the treatments used for COVID-19, such as hydroxychloroquine or corticosteroids, was also considered but found improbable, as no temporary correlation existed between these treatments' administration and the onset of psychosis, with more than a 2-week period between the two events. In fact, in a review of adverse reactions reported in chloroquinetreated patients between 2012 and 2019, 9 no statistically significant reporting of psychosis was found.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".