{"id":"W3134583825","doi":"10.1109/bigcomp51126.2021.00055","title":"Conceptual Modeling and Smart Computing for Big Transportation Data","year":2021,"lang":"en","type":"article","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"University of Manitoba","keywords":"Big data; Computer science; Data science; Popularity; Data modeling; Abstraction; Variety (cybernetics); Smart city; Conceptual model; Intelligent transportation system; Software; World Wide Web; Database; Data mining; Transport engineering; Internet of Things; Engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000160311,0.00004883613,0.00006308535,0.00001862386,0.0000744842,0.0001632619,0.0003896292,0.00001246304,0.000002577844],"category_scores_gemma":[0.00001107811,0.00004697444,0.00001043459,0.00009449142,0.00001226281,0.0005817675,0.0001660486,0.00002384242,0.000001662823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002237898,"about_ca_system_score_gemma":0.00001830235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001857114,"about_ca_topic_score_gemma":0.00005089822,"domain_scores_codex":[0.9993785,0.000007822403,0.0001093292,0.0003179481,0.0000796852,0.0001067314],"domain_scores_gemma":[0.9995119,0.00003563746,0.00001777548,0.0003699717,0.00003783542,0.00002687458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003075064,0.00005112878,0.0007594647,0.00004416626,0.00004517041,0.00001913179,0.001000641,0.002178537,0.0002044824,0.4683512,0.004001072,0.523342],"study_design_scores_gemma":[0.0002431213,0.000008146424,0.0001441349,0.000006154383,0.000006093233,7.307227e-7,0.0002096227,0.991833,0.00009499324,0.0007953219,0.006587501,0.00007114634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008701765,0.00007650661,0.9899812,0.0004762561,0.0002528918,0.00006806702,0.00002888079,0.00006597079,0.0003484589],"genre_scores_gemma":[0.4515971,0.000021892,0.5465112,0.0005148199,0.0001363429,0.000001910029,0.0008220372,0.000005083239,0.0003895923],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9896545,"threshold_uncertainty_score":0.1915562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1096690338744266,"score_gpt":0.288619403781572,"score_spread":0.1789503699071454,"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."}}