{"id":"W2973641207","doi":"10.3390/su11195143","title":"A Two-Stage Restoration Resource Allocation Model for Enhancing the Resilience of Interdependent Infrastructure Systems","year":2019,"lang":"en","type":"article","venue":"Sustainability","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Natural Science Foundation of China","keywords":"Interdependence; Resilience (materials science); Resource allocation; Resource (disambiguation); Process (computing); Computer science; Environmental economics; Risk analysis (engineering); Critical infrastructure; Resource management (computing); Business; Economics; Computer security; Distributed computing","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":[],"consensus_categories":[],"category_scores_codex":[0.001475252,0.0001669339,0.000255348,0.00009062779,0.0001183176,0.0000505531,0.0003355775,0.00009023018,0.00001270935],"category_scores_gemma":[0.0005088,0.000126797,0.0001225288,0.0002878735,0.0001075886,0.0002484649,0.00005418673,0.0002235735,0.000001468455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007594109,"about_ca_system_score_gemma":0.0001809488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001179959,"about_ca_topic_score_gemma":0.0002685915,"domain_scores_codex":[0.9984698,0.0001544261,0.0005189772,0.0002928254,0.0002801485,0.0002838303],"domain_scores_gemma":[0.9983431,0.0001987273,0.0001221057,0.0007614318,0.0005309447,0.00004373921],"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":[0.00003764535,0.000008075233,0.002047142,0.0008198761,0.00001883487,1.457778e-7,0.001701704,0.9854973,0.004067333,0.00470293,0.00006886599,0.001030134],"study_design_scores_gemma":[0.0002049927,0.00003770581,0.002507083,0.00002489508,0.00002575459,9.503418e-7,0.006526347,0.9831805,0.003205563,0.003767609,0.0003822319,0.0001364218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5768051,0.00007357857,0.4216785,0.00008637588,0.00009143014,0.000852016,0.0000119356,0.00005752223,0.0003435948],"genre_scores_gemma":[0.9991698,0.000002732469,0.0003636889,0.0000148825,0.00005014953,0.00007193295,0.00001596344,0.0000170741,0.000293805],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4223647,"threshold_uncertainty_score":0.5170631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004464248155351316,"score_gpt":0.2426571793768074,"score_spread":0.2381929312214561,"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."}}