Multiple Outbreaks Resulting from Asymptomatic Infection in Spreading of COVID-19
Bibliographic record
Abstract
Abstract In this paper, we establish a compartmental model for the transmission of COVID-19 with both symptomatic and asymptomatic infections. The difference is that in our model, we consider the infection caused by multiple contacts with asymptomatic infected population. Through the dynamic analysis of the model, we found that when there is only one contact with an asymptomatic infected people, the system has a unique threshold to control the disease. When there is two contact with asymptomatic infected population, the system will undergo forward bifurcation, backward bifurcation, saddle-node bifurcation, supercritical Hopf bifurcation, subcritical Hopf bifurcation, and Bogdanov-Takens bifurcation with codimension 2. Finally, we give The complete bifurcation diagram and global phase diagram of the system, and the biological significance of our results are also given.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".