Histopathologic Findings of Coronavirus in Lung: A Mini-Review
Bibliographic record
Abstract
Coronaviruses (CoVs) are important human and animal pathogens. There have been several outbreaks of lung involvement by this category of viruses in the world, ie, severe acute respiratory syndrome (SARS-CoV-1) in 2002 and 2003, the Middle East respiratory syndrome (MERS-CoV) in 2012, and the new coronavirus (2019-nCoV) outbreak of pneumonia from Wuhan, China, since December 2019. There have been several studies about the clinical features and imaging features, but very few reports have been published about pathologic findings in lung tissue, which was partly because of the lack of tissue diagnosis secondary to suddenness of the outbreak. Overall, less than 30 reports have been published in the literature about histologic findings of lung in these viruses, so far. In this report, we will review the published reports about the histopathologic findings of lung tissue in the patients infected with SARS-CoV-2 in comparison with 2 other coronaviruses that have caused outbreaks, ie, SARS-CoV-1 and MERS-CoV.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".