{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003849969,0.0009467436,0.0007531306,0.002340961,0.001903713,0.005845528,0.003150813,0.001750356,0.003160898],"category_scores_gemma":[0.008173781,0.0007487672,0.002981846,0.003820258,0.003870624,0.008758821,0.004289538,0.003606917,0.0007458573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004232576,"about_ca_system_score_gemma":0.004015685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0198061,"about_ca_topic_score_gemma":0.0212627,"domain_scores_codex":[0.9972937,0.001134546,0.0002417729,0.0004369167,0.0007004464,0.0001926205],"domain_scores_gemma":[0.9966702,0.001181689,0.0002236847,0.001139021,0.000513654,0.0002717536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000078595,0.00001388577,0.0003690777,0.00006007902,0.00001754757,0.00006721885,0.000326314,0.01717512,0.0001682008,0.9737458,0.002040004,0.006008859],"study_design_scores_gemma":[0.00001014163,0.00001249073,0.0002255482,0.00006276174,0.00002141013,0.0000970887,0.0003405668,0.1935066,0.0002905896,0.7632043,0.04220709,0.00002143974],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003898038,0.000580785,0.9842815,0.003740855,0.0001163354,0.0001245257,0.0004705749,0.0002874214,0.006499892],"genre_scores_gemma":[0.155361,0.001484172,0.8368433,0.0008127923,0.0002019942,0.0005412002,0.001614215,0.0001583041,0.002982994],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0198061,"threshold_uncertainty_score":0.03938162,"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."}}