arXiv (All)
open access
Event-Based Early Warning of Vineyard Disease Risk from Environmental Time Series
Accurate early warning of vineyard disease risk from environmental observations is essential for timely intervention and more sustainable crop protection. However, many existing studies formulate disease prediction as daily presence classification, which can favor persistence-driven predictions and
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Occupational Risk Profiles for Infectious Disease Transmission in the Philippines: A Data-Driven Clustering Analysis#266316
- Automated model discovery based on COVID-19 epidemiological data from Thuringia, Germany.#1166957
- Data and scripts from: Pathogen spillover driven by rapid changes in bat ecology. Food shortage regression tree model#493649
- ASSESSMENT OF OCCUPATIONAL EXPOSURES IN COMMUNITY-BASED CASE-CONTROL STUDIES#383957
- Early warning indicators of spatial epidemics from gauge mediated contagion: a statistical mechanics approach applied to COVID19 in Germany#614915
Record · ID 1052153
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive