Interactions of viral pathogens on hospital admissions for pneumonia, croup and chronic obstructive pulmonary diseases: results of a multivariate time-series analysis
Bibliographic record
Abstract
Co-circulation of respiratory syncytial virus (RSV) and influenza has made the partitioning of morbidity and mortality from each virus difficult. Given the interaction between chronic obstructive lung disease (COPD) and pneumonia, often one can be mistaken for the other. Multivariate time-series methodology was applied to examine the impact of RSV and influenza on hospital admissions for bronchiolitis, pneumonia, and COPD. The Granger Causality Test, used to determine the causal relationship among series, showed that COPD and pneumonia are not influenced by RSV (P=0.2999 and 0.7725), but RSV does influence bronchiolitis (P=0.0001). Influenza was found to influence COPD, pneumonia, and bronchiolitis (P<0.0001). The use of multivariate time series and Granger causality applied to epidemiological data clearly illustrates the significant contribution of influenza and RSV to morbidity in the population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".