{"id":"W3136477615","doi":"10.3390/su13063577","title":"Community Assessment of Flood Risks and Early Warning System in Ratu Watershed, Koshi Basin, Nepal","year":2021,"lang":"en","type":"article","venue":"Sustainability","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centennial College","funders":"","keywords":"Flood myth; Warning system; Early warning system; Environmental planning; Preparedness; Vulnerability (computing); Flooding (psychology); Community network; Geography; Flood warning; Environmental resource management; Water resource management; Environmental science; Engineering; Computer security; Computer science; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001375451,0.0001664524,0.0001751448,0.001836292,0.001241831,0.001140721,0.0003763145,0.000394658,0.001395236],"category_scores_gemma":[0.003989174,0.0001103469,0.0001491042,0.001084657,0.0007825381,0.0008562649,0.001763723,0.0002801389,0.00008463524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001731921,"about_ca_system_score_gemma":0.002691109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02900998,"about_ca_topic_score_gemma":0.05745237,"domain_scores_codex":[0.9990278,0.0005681563,0.00004196978,0.00005546391,0.0001826725,0.0001239051],"domain_scores_gemma":[0.9979569,0.0007245284,0.0003543135,0.00004872612,0.0006435367,0.0002721063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002490154,0.0008906238,0.7545977,0.0003831573,0.0001234204,0.003144323,0.125743,0.004814139,0.004555133,0.004502153,0.001870152,0.0991271],"study_design_scores_gemma":[0.00002648745,0.0008340452,0.6758142,0.0002120103,0.00006959931,0.0005605475,0.2970869,0.01513579,0.001692133,0.001871844,0.006612089,0.00008439415],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970631,0.00002484195,0.0003493545,0.00009790498,0.00000120723,0.0001073992,0.00006510114,0.000004414205,0.002286738],"genre_scores_gemma":[0.9989902,0.00002722098,0.0005032012,0.00001062462,6.371452e-7,0.00007447918,0.00003444734,8.461654e-7,0.0003583478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02900998,"threshold_uncertainty_score":0.05768222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01504646091597397,"score_gpt":0.2855116270987452,"score_spread":0.2704651661827712,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}