{"id":"W3157594375","doi":"10.1016/j.jhydrol.2021.126383","title":"Characterizing natural drivers of water-induced disasters in a rain-fed watershed: Hydro-climatic extremes in the Extended East Rapti Watershed, Nepal","year":2021,"lang":"en","type":"article","venue":"Journal of Hydrology","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Precipitation; Environmental science; Watershed; Flooding (psychology); Climate change; Climatology; Hydrology (agriculture); Period (music); Drainage basin; Physical geography; Geography; Geology; Meteorology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000196485,0.000103471,0.0001477418,0.0005518668,0.0004457212,0.0006689545,0.0004680443,0.0003389728,0.0007870938],"category_scores_gemma":[0.0006696102,0.0001778206,0.000217424,0.0008240211,0.0004141142,0.000412662,0.0008180111,0.0003515757,0.00009608849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008282278,"about_ca_system_score_gemma":0.0008199489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05371503,"about_ca_topic_score_gemma":0.1038804,"domain_scores_codex":[0.9998661,0.00003460424,0.00001030332,0.00002580644,0.00001480521,0.00004840461],"domain_scores_gemma":[0.9995999,0.0001387721,0.0000995562,0.00002253319,0.00004594386,0.00009337682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005753248,0.0001135993,0.9934156,0.000008715338,0.00004250862,0.0006247216,0.001423958,0.001025642,0.0009879635,0.0002332015,0.0001414319,0.001925232],"study_design_scores_gemma":[0.000002767149,0.00002322385,0.9938403,0.000002701635,0.000008163898,0.00009098931,0.003133538,0.002619533,0.0000758263,0.0000880533,0.0001101377,0.000004707469],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997111,0.000003345316,0.00002700439,0.00001749927,2.633296e-7,0.0000034404,0.00007028467,9.586037e-7,0.0001661799],"genre_scores_gemma":[0.9997885,0.00000870773,0.00002660947,0.00000446583,8.093111e-7,0.000005207712,0.0000825286,5.559954e-7,0.00008255521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05371503,"threshold_uncertainty_score":0.1068047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01389749227823046,"score_gpt":0.2358377218738795,"score_spread":0.221940229595649,"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."}}