{"id":"W4324118142","doi":"10.1109/bigdatase56411.2022.00013","title":"A Big Data Science Solution for Transportation Analytics with Meteorological Data","year":2022,"lang":"en","type":"article","venue":"","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Big data; Data analysis; Computer science; Data science; Analytics; Snow; Variety (cybernetics); Real-time data; Meteorology; Data mining; Geography; World Wide Web","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":[0.0004271117,0.0000483437,0.00005123925,0.00008828025,0.0001366348,0.00002049688,0.0007057315,0.000009835167,0.00001692021],"category_scores_gemma":[0.000008154184,0.00004096489,0.000006047377,0.0002996652,0.00004408584,0.0003386315,0.0001073398,0.00005542976,4.718161e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002933241,"about_ca_system_score_gemma":0.00001900072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008810963,"about_ca_topic_score_gemma":0.0001062177,"domain_scores_codex":[0.999389,0.000004286904,0.00008733547,0.0002235144,0.0001791648,0.0001167093],"domain_scores_gemma":[0.9993684,0.00001083398,0.00001202878,0.0005703016,0.00001316664,0.00002524486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001342471,0.0002176071,0.0004193886,0.0001184472,0.0001675265,0.00001004959,0.0001886824,0.08620094,0.006219902,0.03795476,0.507811,0.3605575],"study_design_scores_gemma":[0.0001475009,0.00007048219,0.0007500207,9.112272e-7,0.00003335567,0.000001010593,0.00005690655,0.9032078,0.00009022895,0.00002814167,0.09555223,0.00006144959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001539644,0.00001566539,0.9943378,0.0001552931,0.0001403288,0.0002149435,0.0004605712,0.002005116,0.001130644],"genre_scores_gemma":[0.970769,0.0000191715,0.02761091,0.00007088995,0.00002283445,0.00003628622,0.001436141,0.000006301735,0.00002841031],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9692294,"threshold_uncertainty_score":0.16705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1160942678487804,"score_gpt":0.2774238267985347,"score_spread":0.1613295589497543,"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."}}