{"id":"W2801449844","doi":"10.1007/s12205-018-1314-x","title":"Sustainable Management Framework for Transportation Assets: Application to Urban Pavement Networks","year":2018,"lang":"en","type":"article","venue":"KSCE Journal of Civil Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Interurban; Asset management; Asset (computer security); Sustainable development; Sustainable management; Business; Environmental resource management; Transport engineering; Risk analysis (engineering); Computer science; Engineering; Sustainability; Economics; Computer security","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":[0.0002641616,0.000147858,0.0001752241,0.0001739242,0.0000512648,0.00004315333,0.0001725037,0.00007148758,0.000007947197],"category_scores_gemma":[0.00001707675,0.0001492673,0.00007651583,0.0002223471,0.000006210103,0.0001646333,0.000007763389,0.0001662805,0.000001642729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001872461,"about_ca_system_score_gemma":0.000007104961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001316553,"about_ca_topic_score_gemma":0.000007834165,"domain_scores_codex":[0.9990095,0.000002794906,0.000356796,0.00009648966,0.000175887,0.0003585265],"domain_scores_gemma":[0.9994741,0.00002942428,0.00007207414,0.0001357571,0.000187006,0.0001016409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001944247,0.000008019221,0.0001361086,0.0002295614,0.00009660565,0.000008950011,0.0004558551,0.97825,0.001344803,0.0129723,0.003361865,0.003116442],"study_design_scores_gemma":[0.002006867,0.0009558439,0.01899605,0.001868642,0.0003855698,0.00003247223,0.001607788,0.4400728,0.02452714,0.006506242,0.5016327,0.001407823],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01369157,0.0001754592,0.9845465,0.00004015856,0.001025675,0.0002971051,0.000001926154,0.00007399862,0.0001475792],"genre_scores_gemma":[0.9513649,0.00003753049,0.04682365,0.00003587256,0.001597985,0.00004528802,0.000003493572,0.00004513991,0.00004610217],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9377229,"threshold_uncertainty_score":0.6086943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002774168494678476,"score_gpt":0.2064115708035098,"score_spread":0.2036374023088313,"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."}}