{"id":"W4399147174","doi":"10.1109/trustcom60117.2023.00324","title":"A Big Data Science and Engineering Solution for Transit Performance Analytics","year":2023,"lang":"en","type":"article","venue":"","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"University of Manitoba","keywords":"Public transport; Big data; Destinations; Transit (satellite); Analytics; Transport engineering; Computer science; Usability; Work (physics); Appeal; Data analysis; Data science; Engineering; Tourism; Geography; Political science","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":[0.004029023,0.002445679,0.001354816,0.003956409,0.001351019,0.005301274,0.003799441,0.002218838,0.004139205],"category_scores_gemma":[0.02241644,0.001199358,0.002147648,0.004756827,0.0009212567,0.006974999,0.005796516,0.004527858,0.003880388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009554388,"about_ca_system_score_gemma":0.002187532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003214994,"about_ca_topic_score_gemma":0.004146899,"domain_scores_codex":[0.9948571,0.0007737516,0.0006222418,0.0009867911,0.00251772,0.0002424189],"domain_scores_gemma":[0.9867467,0.00393058,0.001079332,0.004224235,0.003144938,0.0008741252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006834665,0.0009167911,0.01515491,0.002030552,0.0007982653,0.001993663,0.001792179,0.05625874,0.02127527,0.07445597,0.1572282,0.6674119],"study_design_scores_gemma":[0.000127011,0.000175555,0.004384854,0.0003693111,0.0001328567,0.0006209288,0.001200655,0.6161098,0.01302913,0.2105922,0.1530628,0.0001948944],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004738755,0.0006166106,0.9470535,0.004728132,0.0004856764,0.0007079751,0.00779467,0.02840984,0.005464782],"genre_scores_gemma":[0.09028711,0.001030844,0.8825992,0.001719363,0.0004302156,0.0009988281,0.01838699,0.001609434,0.002937965],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005301274,"threshold_uncertainty_score":0.02130777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1230710030310321,"score_gpt":0.3265146481812199,"score_spread":0.2034436451501878,"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."}}