{"data":{"full_name":"Harshiljainn/Yield_Sense","name":"Yield_Sense","description":"Yield Sense is a dual-country machine learning pipeline (India & USA) that predicts wheat yields under extreme weather conditions. Built with Gradient Boosting and Random Forest models, it features an interactive Streamlit dashboard to simulate climate crises and assess regional food security risks.","stars":0.0,"forks":0.0,"language":"Jupyter Notebook","license":null,"archived":0.0,"subcategory":"crop-yield-prediction","last_pushed_at":"2026-03-13T18:48:31+00:00","pypi_package":null,"npm_package":null,"downloads_monthly":0.0,"dependency_count":0.0,"commits_30d":null,"reverse_dep_count":0.0,"maintenance_score":13.0,"adoption_score":0.0,"maturity_score":1.0,"community_score":0.0,"quality_score":14.0,"quality_tier":"experimental","risk_flags":"['no_license', 'no_package', 'no_dependents']"},"meta":{"timestamp":"2026-04-08T07:04:20.559361+00:00"}}