{"id":"W4410064215","doi":"10.1038/s41598-025-98714-5","title":"Enhancing community resilience to ice-jam floods through individuals’ mitigation efforts","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"","keywords":"Flood mitigation; Flood myth; Business; Incentive; Environmental planning; Flooding (psychology); Community resilience; Psychological intervention; Resilience (materials science); Psychological resilience; Environmental resource management; Damages; Risk analysis (engineering); Computer science; Psychology; Political science; Economics; Geography","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.005875807,0.0001459848,0.0001851455,0.0002594742,0.003589646,0.0009697584,0.0006293341,0.00008646522,0.0001233173],"category_scores_gemma":[0.001069773,0.0001418881,0.00008028007,0.002257121,0.0008300325,0.0007993585,0.0003941995,0.0002137681,0.00006962099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001261538,"about_ca_system_score_gemma":0.0003679015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001597083,"about_ca_topic_score_gemma":0.006005059,"domain_scores_codex":[0.9968998,0.0003930839,0.0005299825,0.0006158325,0.001012528,0.0005487483],"domain_scores_gemma":[0.9983019,0.0001306727,0.0002163477,0.001003465,0.0002011329,0.0001465257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002604651,0.0009689402,0.1572128,0.0004243889,0.0001291754,0.0002618849,0.3376794,0.001080572,0.03354936,0.09217488,0.3312555,0.04523708],"study_design_scores_gemma":[0.0001493657,0.00004182549,0.02603788,0.0005169258,0.00005596673,0.000004360422,0.03564993,0.00001725592,0.02728882,0.1121262,0.7976456,0.0004659162],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7608228,0.0000673384,0.002278547,0.001166797,0.007884579,0.0006352031,9.203375e-7,0.0001482811,0.2269956],"genre_scores_gemma":[0.9447354,0.000005872625,0.001368341,0.0003995941,0.00006824257,0.00004106899,0.00001384344,0.000006326359,0.05336129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4663901,"threshold_uncertainty_score":0.9977075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01801266048215002,"score_gpt":0.323943307800424,"score_spread":0.305930647318274,"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."}}