Upsurge of Powassan virus disease in northeastern United States: a public health concern—a short communication
Bibliographic record
Abstract
primarily transmitted through ticks in North America which is a significant public health threat in the northeastern United States. POWV infection spans from Ontario to the Mid-Atlantic, Northeast, and Midwest regions in the USA. Climate change, ecological factors, and human-related changes, including shifts in migration and agriculture, contribute to the dissemination of POWV. Symptoms include sore throat, fatigue, headache, and severe neuroinvasive conditions. Specialized attention is required for diagnosing and managing. MRI scans detect central nervous system abnormalities, while neuromonitoring identifies metabolic distress. Severe cases may necessitate ICU hospitalisation with continuous monitoring. Prevention measures, such as awareness, controlling mammals, and protecting pets, reduce POWV infection risk. The recent outbreak of POWV in Maine, USA, highlights the importance of worldwide collaboration for prevention. With the global prevalence of POWV increasing due to climate and socioeconomic changes, implementing preventative measures and promoting awareness are crucial in reducing infection risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".