{"id":"W4385658832","doi":"10.1111/jfr3.12936","title":"Preparing for severe flooding: Flood risk management research leading to better flood preparedness","year":2023,"lang":"en","type":"article","venue":"Journal of Flood Risk Management","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Flood myth; Flooding (psychology); Preparedness; Damages; Flood mitigation; Geography; China; Water resource management; Environmental science; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004838615,0.0008279785,0.0007722169,0.002348149,0.001775269,0.006836563,0.001461435,0.001799326,0.01314754],"category_scores_gemma":[0.01503888,0.0002960401,0.0007668118,0.003230227,0.001864075,0.006680183,0.001740532,0.003679358,0.002524859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00332164,"about_ca_system_score_gemma":0.008581294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01963074,"about_ca_topic_score_gemma":0.02756878,"domain_scores_codex":[0.9985598,0.0006899685,0.00005908759,0.000153142,0.0003230899,0.0002149716],"domain_scores_gemma":[0.9910051,0.004685003,0.0007596048,0.0003003684,0.002279109,0.0009708746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000161564,0.0008895662,0.02589463,0.003737808,0.0002050385,0.0004343622,0.005899962,0.004705058,0.0005095455,0.1078189,0.1113526,0.7383909],"study_design_scores_gemma":[0.00008069826,0.0009236647,0.0472757,0.02004016,0.0004757505,0.0007061198,0.05855871,0.01535734,0.001020169,0.3713729,0.4838986,0.0002902655],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.07385794,0.4598654,0.02794519,0.2839075,0.004011409,0.0004265104,0.001218093,0.0004456621,0.1483223],"genre_scores_gemma":[0.4274043,0.5174379,0.02761616,0.009692139,0.002231393,0.000291446,0.0008625847,0.0001347218,0.0143294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01963074,"threshold_uncertainty_score":0.04398286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02928553379984516,"score_gpt":0.3299839540317172,"score_spread":0.300698420231872,"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."}}