Changing dynamics of psychoneuroimmunology during the COVID-19 pandemic
Bibliographic record
Abstract
The Coronavirus Disease-2019 (COVID-19) pandemic has led to a global health care crisis. Emerging research suggest an unanticipated impact of COVID-19 on mental and/or psychological health of both the general community and affected individuals. The fear of the COVID-19 epidemic and the consequent lockdown and economic crisis has led to globally increased psychological distress. The biological bases of immediate and new onset of psychiatric symptoms in individuals with COVID-19 are not yet known. COVID-19 infection may lead to activated immune-inflammatory pathways and a cytokine storm. Activated immune-inflammatory pathways, especially chronic low-grade inflammation, are associated with major psychiatric disorders in at least a subset of individuals. We propose that both the (sub)chronic inflammatory response and cytokine storm might crucially be involved in the immediate manifestation of neuropsychiatric symptoms in individuals with COVID-19 infection as well as heightened expression of psychiatric symptoms in COVID-19 infected individuals with prior psychiatric conditions. These events might expand concepts in psychoneuroimmunology, with the importance of chronic-low grade inflammation augmented by the cytokine storm hypothesis. Additionally, this might augment and refine diagnosis and prognostic management as well as treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".