{"id":"W2524647919","doi":"10.5055/jem.2016.0289","title":"Building resilient communities: A facilitated discussion","year":2016,"lang":"en","type":"article","venue":"Journal of Emergency Management","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Columbian Hospital","funders":"","keywords":"Resilience (materials science); Public relations; Community resilience; Government (linguistics); Emergency management; Variety (cybernetics); Context (archaeology); Sustainability; Business; Political science; Environmental resource management; Community engagement; Disaster recovery; Environmental planning; Knowledge management; Resource (disambiguation); Geography; Computer science; Economics","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":[0.04601382,0.001793513,0.0009678537,0.002187291,0.03921659,0.01079752,0.005283487,0.008891322,0.01597776],"category_scores_gemma":[0.04655229,0.001070391,0.001390731,0.001087274,0.01525494,0.01373091,0.04022953,0.01103243,0.002936973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006283557,"about_ca_system_score_gemma":0.01135843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002809191,"about_ca_topic_score_gemma":0.004232972,"domain_scores_codex":[0.9590249,0.03395975,0.0006791323,0.001635734,0.001947389,0.002753087],"domain_scores_gemma":[0.9562849,0.02802049,0.001362102,0.002281745,0.003688067,0.008362751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002033697,0.0004770724,0.0007797381,0.0004700521,0.00001834073,0.003091981,0.9004051,0.0003408763,0.001456803,0.02918353,0.03846784,0.02510534],"study_design_scores_gemma":[0.0001479183,0.0001897446,0.000432634,0.0004002051,0.00001729369,0.0004290854,0.6028396,0.0005455097,0.0009016986,0.02037993,0.3736309,0.00008546875],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4263312,0.00287521,0.1205413,0.2087119,0.0139075,0.01889203,0.001165402,0.002048778,0.2055267],"genre_scores_gemma":[0.8551499,0.001372689,0.05721276,0.01492019,0.001258639,0.01123232,0.0003199317,0.00043908,0.05809442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04601382,"threshold_uncertainty_score":0.2433472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03718815016618588,"score_gpt":0.3419772063862296,"score_spread":0.3047890562200437,"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."}}