No new community COVID-19 infection in four consecutive weeks: what lesson can be learned from Vietnam
Bibliographic record
Abstract
Sharing a common land border with China, Vietnam has faced a high risk of transmission of Coronavirus Disease 2019 (COVID-19). Rapid decision making and robust public health measures were established by the Vietnamese Government to control the situation. As of 17 May 2020, Vietnam reported 320 total confirmed cases of COVID-19, of whom 260 had fully recovered, while the remaining 60 cases were still under treatment. Noteworthy, the current data still confirms zero deaths and within the last 32 consecutive days prior to this submission, there have been no new infections in the country. Valuable lessons from Severe Acute Respiratory Syndrome in 2003 such as use of quarantine, early recognition and quick response to the infection, and increased awareness of its citizens have put Vietnam in a somewhat better position against COVID-19 compared to other places. Vietnam, at the current time, mulls declaring an end of the current COVID-19 outbreak.
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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 | 0.004 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".