{"id":"W4400014188","doi":"10.2139/ssrn.4869827","title":"Consensus Reaching-Based Decision Model for Assessing Resilient Urban Public Health Safety Ecosystem with Social Network Analysis","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Knowledge Management and Technology","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Social network analysis; Public health; Environmental planning; Decision analysis; Ecosystem health; Environmental resource management; Ecosystem; Ecosystem services; Business; Computer science; Geography; Environmental science; Economics; Ecology; Medicine; Social media","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005877566,0.001743318,0.003219179,0.002919795,0.001356134,0.00275264,0.003534331,0.003856292,0.006592975],"category_scores_gemma":[0.01119657,0.0009922879,0.001954324,0.001888443,0.001935301,0.003281904,0.00295646,0.002173891,0.0005376342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003561659,"about_ca_system_score_gemma":0.003718819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01862329,"about_ca_topic_score_gemma":0.009226219,"domain_scores_codex":[0.9972001,0.001140906,0.0001328569,0.000741882,0.0003817692,0.0004023429],"domain_scores_gemma":[0.9910586,0.00668844,0.0005779131,0.0001962616,0.00105034,0.0004283506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006075675,0.00003641366,0.0005638581,0.00004215868,0.00004958093,0.00004819602,0.00004685418,0.9840893,0.0002097355,0.01037121,0.0003198038,0.004162167],"study_design_scores_gemma":[0.000003932772,0.00001097577,0.0000375553,0.000002946817,0.000008010523,0.000003104265,0.0000086749,0.9962839,0.00003259467,0.003561673,0.000042878,0.000003865503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05950507,0.0002161517,0.9332993,0.0006932526,0.00007811493,0.0002085892,0.0003395281,0.0002824737,0.005377475],"genre_scores_gemma":[0.9255822,0.0001683876,0.06793761,0.0001462748,0.00006001725,0.0004607773,0.000423582,0.00005832743,0.005162793],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01862329,"threshold_uncertainty_score":0.0370298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07498968392419118,"score_gpt":0.3736192632325473,"score_spread":0.2986295793083562,"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."}}