{"id":"W2959691222","doi":"10.3390/su11143822","title":"Applying Machine Learning and Statistical Approaches for Travel Time Estimation in Partial Network Coverage","year":2019,"lang":"en","type":"article","venue":"Sustainability","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Kuwait University","keywords":"VisSim; Artificial neural network; Computer science; Statistical model; Microsimulation; Artificial intelligence; Random forest; Machine learning; Simulation; Data mining; Engineering","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":[0.0007156886,0.0008603688,0.0005820814,0.001263264,0.0001966889,0.0005230782,0.0005531033,0.0005467349,0.000367136],"category_scores_gemma":[0.00421574,0.0003621878,0.0005562906,0.001259869,0.000264475,0.001033547,0.0003587286,0.0004204263,0.0001003125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005284111,"about_ca_system_score_gemma":0.0005057884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01006542,"about_ca_topic_score_gemma":0.00708598,"domain_scores_codex":[0.9996493,0.0001093198,0.00002624081,0.00008544012,0.00009034255,0.00003941493],"domain_scores_gemma":[0.9983298,0.001022419,0.0002537453,0.0001182314,0.0002462543,0.00002958676],"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":[0.00002252366,0.00001337111,0.002666545,0.00002512679,0.0000322317,0.00003185503,0.00001535021,0.9583139,0.0008111162,0.0006274689,0.00008349144,0.03735713],"study_design_scores_gemma":[5.155242e-7,0.000006386686,0.0005904652,0.000001761954,0.00000255116,0.000008236234,0.000003936202,0.9987011,0.0002421255,0.0003884799,0.00005191623,0.000002472928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1087113,0.0003588842,0.8894248,0.00008623526,0.00002753153,0.00002221635,0.0001215141,0.0004763304,0.0007712462],"genre_scores_gemma":[0.9155813,0.0002794156,0.08318012,0.00003147145,0.00003065906,0.00006113335,0.0002614469,0.00003465496,0.0005398079],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01006542,"threshold_uncertainty_score":0.02001363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007311761859455575,"score_gpt":0.225855447914635,"score_spread":0.2185436860551795,"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."}}