{"id":"W1538922767","doi":"10.7916/d8g1681r","title":"Planning for Long‐Term Recovery Before Disaster Strikes: Case Studies of 4 US Cities: A Final Project Report","year":2011,"lang":"en","type":"article","venue":"Columbia Academic Commons (Columbia University)","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Term (time); Environmental planning; Business; History; Operations management; Forensic engineering; Geography; Engineering","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":[0.003653313,0.0009075454,0.0003040145,0.001399834,0.005900677,0.002841766,0.002506916,0.002344264,0.003800995],"category_scores_gemma":[0.005410517,0.0006657902,0.001109783,0.003057701,0.001593789,0.002173884,0.003401825,0.001990512,0.0004587288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01134961,"about_ca_system_score_gemma":0.0164443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2616918,"about_ca_topic_score_gemma":0.4913184,"domain_scores_codex":[0.9979272,0.001181006,0.00006477627,0.00008761003,0.000200059,0.0005392333],"domain_scores_gemma":[0.9966348,0.001117738,0.0003432823,0.0002419487,0.0009362368,0.000726131],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002286682,0.02054264,0.3580101,0.001970682,0.0007855932,0.0465159,0.1138324,0.08751608,0.002949844,0.02944142,0.1136437,0.222505],"study_design_scores_gemma":[0.001380702,0.00543496,0.1617449,0.0007974925,0.0004861428,0.003828522,0.6310813,0.04023286,0.003559982,0.006008677,0.1450244,0.0004200609],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764059,0.0003805962,0.002033109,0.00334739,0.00003084428,0.001384643,0.000887314,0.00008730902,0.0154429],"genre_scores_gemma":[0.9752365,0.001712092,0.009248264,0.0007713867,0.00002128038,0.001808962,0.001392255,0.0000559873,0.009753155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2616918,"threshold_uncertainty_score":0.5203372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1310250203292093,"score_gpt":0.3359273771220714,"score_spread":0.2049023567928621,"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."}}