Bibliographic record
Abstract
West Nile virus (WNV) was detected in the metropolitan New York City (NYC) area during the summer and fall of 1999. Sixty-two human cases, including seven fatalities, were documented. The New York State Department of Health (NYSDOH) initiated and implemented a statewide mosquito and WNV surveillance system. We developed a WNV response plan designed to provide local health departments (LHD) a standardized means to begin to assess basic mosquito population data and to detect WNV circulation in mosquito populations. During the 2000 arbovirus surveillance season, local health agencies collected 317,676 mosquitoes and submitted 9,952 pools for virus testing. NYSDOH polymerase chain reaction (PCR) testing detected 363 WNV-positive pools. Eight species of mosquitoes were found to be infected. Of the 26 counties conducting mosquito surveillance, WNV-positive mosquitoes were detected only in NYC, on Long Island, and in four counties in the lower Hudson River valley region. LHD larval surveillance provided initial or enhanced mosquito habitat location and characterization and mosquito species documentation. Adult mosquito surveillance provided LHD information on species' presence, density, seasonal fluctuations, virus infection, minimum infection ratios (MIR) and indirect data on mosquito control efficacy after larval or adult control interventions. Collective surveillance activities conducted during 1999 and 2000 suggest that WNV has dispersed throughout the state and may affect local health jurisdictions within NYS, adjacent states, and Canada in future years. Vector surveillance will remain a critical component of LHD programs addressing public health concerns related to WNV.
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 | 0.001 | 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 | 0.000 | 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) | 0.004 | 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".