{"id":"W2760254186","doi":"10.1016/b978-0-12-812808-4.00005-5","title":"Risk Management, Response, Relief, Recovery, Reconstruction, and Future Disaster Risk Reduction","year":2017,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Fatalism; Vulnerability (computing); Disaster risk reduction; Risk management; Scale (ratio); Environmental planning; Reduction (mathematics); Risk analysis (engineering); Environmental resource management; Business; Political science; Geography; Computer security; Computer science; Environmental science; Finance; Cartography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001619182,0.0004589908,0.0004448503,0.0003145366,0.002158121,0.0005558045,0.0006197926,0.0004805044,0.0003706283],"category_scores_gemma":[0.00006581154,0.0004346591,0.000233382,0.00002189022,0.001253813,0.0003867567,0.000289268,0.0006290857,0.000222824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001430465,"about_ca_system_score_gemma":0.00008084648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000227139,"about_ca_topic_score_gemma":0.0004464634,"domain_scores_codex":[0.997219,0.0003549226,0.0004723639,0.0009058738,0.0005907117,0.0004570919],"domain_scores_gemma":[0.9975893,0.00007005396,0.001045343,0.0009825475,0.0001073198,0.00020538],"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":[0.000240226,0.000006347902,0.00006888482,0.00004772897,0.0001935469,0.00001531103,0.0027087,2.539574e-7,5.720075e-7,0.01176142,0.002508974,0.982448],"study_design_scores_gemma":[0.0002947348,0.0000645918,0.0005350481,0.0003107327,0.0004003512,0.00001044005,0.001852418,6.191422e-7,5.694594e-7,0.06356757,0.9324704,0.000492564],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0008814191,0.001234858,0.000005494275,0.0004071445,0.00379156,0.0009919397,0.00005685775,0.0001248035,0.9925059],"genre_scores_gemma":[0.0003911473,0.02910889,0.0005436511,0.00004697039,0.002408438,0.00003493663,0.000008999329,0.00006365692,0.9673933],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9819555,"threshold_uncertainty_score":0.9998105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009222162829857002,"score_gpt":0.2491647086386259,"score_spread":0.2399425458087689,"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."}}