Bibliographic record
Abstract
In 2019, COVID-19 had taken place in Wuhan, China, and then cause a global pandemic. In March 2020, the World Health Organization (WHO) declared COVID-19 as pandemic. This disease is caused by a novel coronavirus SARS-CoV-2 belonging to Coronaviridae family. The rapid spreading disease calls for fast and reliable diagnosis tools and effective treatment. Here in this review, we evaluated the most widely used diagnosis tools including reverse transcribed PCR and radiographic imaging. Current treatment approaches have also been discussed. Two major novel therapeutics targeting SARS-CoV-2 with ongoing clinical trials -PF07321332 and Molnupiravirhave been discussed in detail. A rapid spread and alarming data about COVID-19 accumulating and causing death on a daily basis call for fast and reliable diagnostic tools and timely treatment. One of the best diagnostic methods is reverse transcription polymerase chain reaction (RT-PCR). An imaging technique such as CT and X-ray is a supplementary tool for confirming the infection based on the changes in images. As a result of the urgency of pandemic control, various studies have been carried out to develop specific therapeutics targeting SARS-CoV-2. It has been applied with limited success to repurpose several antiviral drugs. Molnupiravir and PF07321332, two recently developed therapeutics, are undergoing clinical trials showing promising antiviral effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".