{"id":"W4224443201","doi":"10.1139/cjce-2021-0539","title":"Relative sea level rise contributions to flood construction levels in British Columbia","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Flood myth; Estimation; Probabilistic logic; Sea level; Environmental science; Computer science; Meteorology; Operations research; Environmental resource management; Hydrology (agriculture); Civil engineering; Physical geography; Geology; Statistics; Geography; Engineering; Mathematics; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0008486398,0.000246956,0.0001922458,0.001490323,0.0008635363,0.00159407,0.0005353601,0.0002514782,0.001759577],"category_scores_gemma":[0.003905432,0.0002514374,0.0002349097,0.003041958,0.0006236272,0.0004337018,0.001035641,0.0005766288,0.0001770082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01166581,"about_ca_system_score_gemma":0.007832276,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9321396,"about_ca_topic_score_gemma":0.964677,"domain_scores_codex":[0.9992167,0.0001582631,0.0000427732,0.00007682022,0.0003679796,0.0001375381],"domain_scores_gemma":[0.9985367,0.0004045138,0.000143013,0.0000764642,0.0007437277,0.00009562749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002442478,0.00003702203,0.6165049,0.0001291264,0.0001390548,0.001187533,0.002009759,0.2393534,0.002943631,0.01269909,0.004088318,0.1206638],"study_design_scores_gemma":[0.00001172109,0.00004298967,0.8415061,0.0001090486,0.00007459667,0.0002939756,0.003197518,0.1360128,0.001826604,0.003032364,0.01375841,0.0001338221],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.976845,0.0003787039,0.003899155,0.0005956843,0.00001114968,0.00001751857,0.001279623,0.00009077208,0.01688247],"genre_scores_gemma":[0.9950258,0.0002718751,0.001125804,0.00002808248,0.000001479074,0.000006661368,0.0005194073,0.00001925914,0.003001682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06786036,"threshold_uncertainty_score":0.13652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007531271836039136,"score_gpt":0.1951267173837646,"score_spread":0.1875954455477255,"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."}}