An overview of post‐COVID‐19 complications
Bibliographic record
Abstract
An overview of post-COVID-19 complicationsThe emergency of coronavirus disease 2019 (COVID-19) has resulted in an incomparable worldwide pandemic.Thus, the World Health Organization (WHO) has declared COVID-19 as a pandemic in 12 March 2020. 1 Amid the acute phase of COVID-19, patients can be presented by several manifestations including cough, fever, nausea, diarrhoea, vomiting, muscles and joints pain, headache, fatigue and anosmia.Moreover, several studies reported that different types of complications occur in multiple body systems during post-viral infection phases. 2 Upon searching three databases (PubMed, Google Scholar and WHO COVID-19 data bases), a recent systematic review found 69 articles from 15 countries reported post-COVID-19 complications among survivors.3 Respiratory complications were identified in 36 studies from several countries (China, Egypt, Germany, Italy, the UK, Netherland, Canada, Saudi Arabia, Iran, France, Spain and the United States). 3 The commonly reported symptoms were breathlessness, lung function abnormalities, pulmonary fibrosis (interstitial thickening and crazy paving), residual ground-glass opacity, abnormal diffusion, pneumonia and pulmonary embolism.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".