{"id":"W4297513501","doi":"10.1080/07011784.2022.2122083","title":"Flood risk assessment data access and equity in Metro Vancouver","year":2022,"lang":"en","type":"article","venue":"Canadian Water Resources Journal / Revue canadienne des ressources hydriques","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Toronto Metropolitan University","funders":"Marine Environmental Observation Prediction and Response Network","keywords":"Equity (law); Flood myth; Business; Environmental planning; Geography; Political science; Archaeology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.003317403,0.0001702959,0.0003165709,0.003482796,0.002406089,0.004707756,0.0009923186,0.0003483387,0.002942936],"category_scores_gemma":[0.02507466,0.0002046512,0.000183506,0.007439004,0.001354424,0.001138551,0.003136085,0.0006376058,0.0002040216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01933855,"about_ca_system_score_gemma":0.01726135,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.95296,"about_ca_topic_score_gemma":0.9642393,"domain_scores_codex":[0.9952433,0.0009226874,0.0002703063,0.0003520563,0.002262266,0.0009494072],"domain_scores_gemma":[0.982104,0.005167418,0.0021865,0.00106571,0.007644949,0.001831362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001198507,0.00008558793,0.9313807,0.0000610519,0.00005137904,0.0002788212,0.01044387,0.00160841,0.0002413436,0.003861468,0.002334045,0.0495335],"study_design_scores_gemma":[0.000009460679,0.00004314518,0.9520159,0.0001172773,0.00002454918,0.0001514903,0.03069973,0.004562373,0.0003678577,0.00167466,0.01029009,0.00004347308],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782954,0.0002353994,0.0005541804,0.0009968443,0.000005421656,0.000108341,0.001656664,0.00001948897,0.01812839],"genre_scores_gemma":[0.9970859,0.0001226397,0.000361816,0.00004184882,0.000002396894,0.00002792764,0.0005999334,0.000006797663,0.001750845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04703999,"threshold_uncertainty_score":0.1403117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03184549892320456,"score_gpt":0.2817244237035537,"score_spread":0.2498789247803491,"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."}}