{"id":"W2307614369","doi":"10.1002/hyp.10853","title":"Ice‐jam flood risk assessment and mapping","year":2016,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Flood myth; Environmental science; Hydrology (agriculture); Flooding (psychology); Flood risk assessment; 100-year flood; Return period; Risk assessment; Hazard analysis; Flood stage; Geology; Geography; Engineering; Geotechnical engineering; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0005400229,0.0002725181,0.0001649759,0.002680626,0.0002874736,0.0009272379,0.000405795,0.000178521,0.001973385],"category_scores_gemma":[0.001068156,0.0001240557,0.0001711453,0.001554488,0.0002060121,0.0002828664,0.0005171975,0.0001317663,0.0001793387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001661006,"about_ca_system_score_gemma":0.001401964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1415623,"about_ca_topic_score_gemma":0.1646897,"domain_scores_codex":[0.9998524,0.00003163408,0.000007634741,0.00001681141,0.00006514718,0.00002631943],"domain_scores_gemma":[0.9997539,0.00005272443,0.00005974381,0.00001645913,0.00008844741,0.00002875794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002102711,0.00009420366,0.2571396,0.0001079881,0.00009135609,0.0004994202,0.0007124179,0.5628754,0.003949354,0.006331004,0.005479106,0.1625098],"study_design_scores_gemma":[0.0000105881,0.00002962644,0.1537366,0.00003485797,0.00002961367,0.00008934983,0.0006145634,0.835906,0.00189377,0.002202824,0.005424831,0.00002746768],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9333015,0.0003049291,0.04252134,0.0001960135,0.000008667232,0.0001515759,0.003439215,0.0007983437,0.01927846],"genre_scores_gemma":[0.9893449,0.0001230364,0.008269254,0.000004351863,0.000002766212,0.00001956554,0.0007677104,0.00001384423,0.001454713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1415623,"threshold_uncertainty_score":0.2814766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01668506470013677,"score_gpt":0.2271416532042916,"score_spread":0.2104565885041548,"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."}}