{"id":"W4403320432","doi":"10.5337/2017","title":"Mapping Multiple Climate-related Hazards in South Asia","year":2017,"lang":"en","type":"report","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"United Nations University Institute for Water, Environment, and Health","funders":"","keywords":"Geography; Climatology; Physical geography; Environmental science; Geology","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":[0.0008121754,0.0005474968,0.0002929192,0.002296498,0.0004343329,0.001269941,0.0004843585,0.0003751862,0.001409487],"category_scores_gemma":[0.0006270727,0.0002475997,0.0005312655,0.002996442,0.0003055105,0.001334953,0.002408797,0.0003790124,0.0002087429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009018596,"about_ca_system_score_gemma":0.002304957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0215057,"about_ca_topic_score_gemma":0.02342476,"domain_scores_codex":[0.9997044,0.00004971288,0.00002182683,0.00004467041,0.0001242654,0.00005509882],"domain_scores_gemma":[0.9995199,0.0001283947,0.0001358329,0.00004691369,0.0001158395,0.00005309032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002567708,0.0002160848,0.5796753,0.001167103,0.0004328013,0.003848158,0.01065911,0.0988346,0.01954543,0.01409511,0.004368675,0.266901],"study_design_scores_gemma":[0.0000722152,0.0004294571,0.7559678,0.0007449687,0.0005084839,0.003180942,0.03287941,0.106239,0.01338467,0.02600294,0.06037664,0.000213433],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9448399,0.002155159,0.01971847,0.0009835347,0.00003269098,0.000176788,0.00330295,0.0001420578,0.02864847],"genre_scores_gemma":[0.9746838,0.003120069,0.01580472,0.00006630765,0.00001804108,0.000111669,0.002406204,0.00003035574,0.003758871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0215057,"threshold_uncertainty_score":0.04276109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01724770982127623,"score_gpt":0.2459519982061753,"score_spread":0.2287042883848991,"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."}}