{"id":"W2904865539","doi":"10.1080/17477891.2018.1549970","title":"Assessing community resilience: mapping the community rating system (CRS) against the 6C-4R frameworks","year":2018,"lang":"en","type":"article","venue":"Environmental Hazards","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Community resilience; Environmental resource management; Flood myth; Resilience (materials science); Environmental planning; Risk analysis (engineering); Natural hazard; Social capital; Psychological resilience; Business; Computer science; Redundancy (engineering); Sociology; Geography; Economics; Psychology; Social psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007095471,0.0006836082,0.0005782328,0.01158941,0.001086507,0.002868081,0.0009803206,0.0007065423,0.002358195],"category_scores_gemma":[0.02532702,0.0002234681,0.000727757,0.008802023,0.001755182,0.003247497,0.004755834,0.0008748122,0.0003542783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002743977,"about_ca_system_score_gemma":0.002926943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03004322,"about_ca_topic_score_gemma":0.02894925,"domain_scores_codex":[0.9926991,0.003869014,0.0004589401,0.0007698645,0.001806889,0.0003961525],"domain_scores_gemma":[0.9885126,0.003507359,0.003251094,0.001079616,0.003181533,0.0004677641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002507333,0.0002424094,0.3813535,0.0009055195,0.0004598402,0.0006006737,0.008425153,0.08571847,0.003263899,0.1306552,0.009001568,0.379123],"study_design_scores_gemma":[0.00005340237,0.0008957593,0.4760894,0.001141522,0.0002394018,0.0009445598,0.03648909,0.3252581,0.003006135,0.1045501,0.05087802,0.0004544828],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6441308,0.001135859,0.2607149,0.002566172,0.0001080827,0.001171389,0.003847909,0.0007956289,0.0855291],"genre_scores_gemma":[0.9280113,0.0001693557,0.0703125,0.00006490633,0.00001213379,0.0002278595,0.0006404052,0.00001912657,0.000542358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03004322,"threshold_uncertainty_score":0.05973667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03785574876235772,"score_gpt":0.3031076317894953,"score_spread":0.2652518830271376,"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."}}