An update of coronavirus disease 2019 (COVID-19): an essential brief
Bibliographic record
Abstract
During 2019, the number of patients suffering from cough, fever and reduction of WBC's count increased.At the beginning, this mysterious illness was called "fever with unknown origin" but now, it is known as the 2019 novel coronavirus (2019-nCoV) or the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2).The SARS-CoV-2 is one member of great family of coronaviruses.Coronaviruses are enveloped positive-stranded RNA viruses.The SARS-CoV-2 has some particular structures for infecting, reproducing and causing damage.The SARS-CoV-2 can bind angiotensin-converting enzyme 2 (ACE-2) receptors and cause various difficulties for human.The SARS-CoV-2 can cause both serious and not-serious issues for mankind.Malayan pangolin and bat are the most suspicious candidate for being sources of the SARS-CoV-2.The SARS-CoV-2 can be transmitted by various ways such as transmitting from infected human to healthy human and can make severe pneumonia, which can lead to death.The SARS-CoV-2 can infect different kind of people with different ages, races, and social and economic levels.The SARS-CoV-2 infection can cause various sorts of clinical manifestations like cough and fever and intensity of signs and symptoms depends on sufferer conditions.Clinicians use all of available documents and tests for diagnosing new cases and curing patients with high accuracy.At the present time, there is no particular way for treating SARS-CoV-2 infection.It seems that the best way for standing against the SARS-CoV-2 infection is preventing from it by social distancing and vaccination.This review tries to prepare an essential brief update about SARS-CoV-2 infection.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.009 |
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".