{"id":"W2061575379","doi":"10.1007/s11069-010-9576-8","title":"Debris-flow impact, vulnerability, and response","year":2010,"lang":"en","type":"article","venue":"Natural Hazards","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":130,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Natural hazard; Hazard; Vulnerability (computing); Misappropriation; Landslide; Flooding (psychology); Preparedness; Debris flow; Debris; Environmental planning; Risk analysis (engineering); Forensic engineering; Environmental resource management; Business; Engineering; Environmental science; Computer science; Computer security; Geography","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":[0.000746365,0.0001986803,0.0001691081,0.001003361,0.0004758015,0.001053616,0.0001718782,0.0006310464,0.004919027],"category_scores_gemma":[0.004416481,0.0001864034,0.0001827923,0.0008380764,0.0008633491,0.0007835638,0.0007643561,0.0003490984,0.0002802671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006596395,"about_ca_system_score_gemma":0.0004727533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003448601,"about_ca_topic_score_gemma":0.008990142,"domain_scores_codex":[0.9996129,0.0001555807,0.00002088328,0.00004093499,0.00007922298,0.00009051485],"domain_scores_gemma":[0.9979035,0.001106822,0.0004880711,0.00007490148,0.0001779595,0.0002487196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002733495,0.0002039219,0.9573519,0.00005233781,0.0001193573,0.0004822015,0.0007700769,0.007266413,0.0006586075,0.006425774,0.001086092,0.0253099],"study_design_scores_gemma":[0.00001136274,0.0001540591,0.9755198,0.0000235261,0.00003942426,0.0006383864,0.002413547,0.004290271,0.0002107231,0.01493988,0.001743804,0.00001523833],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864226,0.0009973801,0.0006790793,0.0009310212,0.00001363173,0.0000119626,0.0001596898,0.000008929469,0.01077562],"genre_scores_gemma":[0.999024,0.0002701004,0.00008299918,0.00002641262,0.0000119648,0.00000377684,0.00002748901,0.000001269515,0.0005520178],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004919027,"threshold_uncertainty_score":0.01645577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004235268073613037,"score_gpt":0.2540896233610661,"score_spread":0.2498543552874531,"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."}}