{"id":"W3172192278","doi":"10.1155/2021/5283283","title":"Detecting Invalid Associations between Fare Machines and Metro Stations Using Smart Card Data","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Data mining; Data collection; Data quality; Quality (philosophy); Association (psychology); Isolation (microbiology); Volume (thermodynamics); Engineering; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002124689,0.0007556918,0.0007053232,0.003197184,0.0007031323,0.001564774,0.001129526,0.0007417995,0.001130239],"category_scores_gemma":[0.01139717,0.0003085113,0.0004706519,0.003670746,0.0004856761,0.002267936,0.001476683,0.0007272682,0.0007940729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007164375,"about_ca_system_score_gemma":0.001131818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007575062,"about_ca_topic_score_gemma":0.007996731,"domain_scores_codex":[0.9972066,0.0004571397,0.0003902667,0.0005998425,0.001093962,0.0002520827],"domain_scores_gemma":[0.9902734,0.002213561,0.002301685,0.002278449,0.002633632,0.0002991342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005966707,0.0002907881,0.5460401,0.0004524297,0.0002195123,0.0007347715,0.0008047734,0.05725257,0.01577889,0.005452517,0.006325603,0.3660513],"study_design_scores_gemma":[0.00002759001,0.0002167833,0.2054623,0.0001386945,0.0001372963,0.0005817533,0.001587706,0.7325804,0.03185153,0.009332977,0.0179568,0.0001260925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5130881,0.0005961193,0.4714755,0.0004071761,0.000210667,0.0003362297,0.006748848,0.002544193,0.004593223],"genre_scores_gemma":[0.9033596,0.000180586,0.09025978,0.00006349657,0.00004723135,0.00008672548,0.004935998,0.00005710515,0.001009427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007575062,"threshold_uncertainty_score":0.01506197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07181426420253174,"score_gpt":0.3701012849389659,"score_spread":0.2982870207364342,"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."}}