The successful development and implementation of an off campus triage system during the COVID-19 pandemic in Guangdong, China
Bibliographic record
Abstract
To deal with the public health crisis caused by the coronavirus disease 2019 (COVID-19) outbreak, we developed an off campus triage system at entry points to the outpatient, emergency, and inpatient departments. To enhance this off campus triage system, we implemented intensive staff training and made detailed triage plans with a timely referral. Of the 85,414 patients/visitors who visited The Seventh Affiliated Hospital of Southern Medical University, one of the government-designated hospitals to triage-suspected COVID-19 patients between January 22 and March 10, 2020, 359 patients were triaged to the COVID-19 fever clinic and 1,218 were triaged to the general fever clinic; 187 were suspected of COVID-19 infection and quarantined; and four cases of COVID-19 were confirmed and referred. During the outbreak, no inhospital infection and no complaint from patients and their family members occurred, and up to September 10, 2020, no new cases of COVID-19 in this hospital or its catchment area were detected. The off campus triage system is an effective approach to improve the detection of COVID-19 infection and reduce inhospital cross infection.
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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 | 0.002 | 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) | 0.000 | 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".