{"id":"W4221075351","doi":"10.3390/su14053087","title":"Understanding Flood Risk Perception: A Case Study from Canada","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Flood myth; Risk perception; Floodplain; Flooding (psychology); Climate change; Risk governance; Flood risk management; Geography; Environmental planning; Environmental resource management; Natural hazard; Risk management; Perception; Business; Psychology; Environmental science; Cartography; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006446426,0.0001264913,0.0001219629,0.00002066542,0.00112357,0.00003255001,0.0002067912,0.00001262491,0.008351652],"category_scores_gemma":[0.00005274783,0.0001272945,0.00004038319,0.0002737943,0.0000640208,0.0001162981,0.0009202444,0.0002308076,0.000005457048],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0143732,"about_ca_system_score_gemma":0.0002117164,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9847531,"about_ca_topic_score_gemma":0.9528471,"domain_scores_codex":[0.9981155,0.0004025476,0.0001847472,0.0004586116,0.0005453568,0.0002932577],"domain_scores_gemma":[0.9993195,0.00006287218,0.00006675265,0.0004496307,0.00001132217,0.00008995744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002039397,0.0004258619,0.9774209,0.000004935235,0.00002731542,0.002065328,0.003576554,0.009746538,0.00000175065,0.00003993765,0.005225194,0.00144534],"study_design_scores_gemma":[0.0006366296,0.0002219098,0.4672097,2.912379e-7,0.00007416064,0.00002278333,0.5190862,0.00184981,6.523544e-7,0.006354854,0.004325841,0.0002172108],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963464,0.000006099071,0.0007612584,0.0005404808,0.0002107826,0.0009343727,0.00003333923,0.00004376259,0.001123537],"genre_scores_gemma":[0.9992644,0.00000111236,0.000103448,0.0000803284,0.00002383473,0.0001418546,0.000008122892,0.000009546917,0.0003673311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5155097,"threshold_uncertainty_score":0.9925548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02223613513092191,"score_gpt":0.2465613287590008,"score_spread":0.2243251936280789,"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."}}