{"id":"W2206600317","doi":"","title":"The OPUS Card: Yesterday, Today & Tomorrow","year":2014,"lang":"en","type":"article","venue":"","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Opus; Public transport; Transit (satellite); Yesterday; Smart card; Engineering; Computer science; Transport engineering; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003906534,0.0006712311,0.0002288629,0.0007560242,0.001604324,0.004160114,0.0006936665,0.0009187462,0.1232782],"category_scores_gemma":[0.001184758,0.0002147221,0.0001538601,0.001428971,0.0007885739,0.002519709,0.00126255,0.000875363,0.03420955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002807552,"about_ca_system_score_gemma":0.003076853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07948752,"about_ca_topic_score_gemma":0.1151773,"domain_scores_codex":[0.9995589,0.00004329453,0.00001210791,0.00004740463,0.0002108922,0.0001273665],"domain_scores_gemma":[0.9995957,0.00002771616,0.0000225512,0.00002484671,0.000207761,0.0001213611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001404312,0.00002618977,0.002315111,0.0001549651,0.000002989329,0.0002880032,0.0005956257,0.000238217,0.001717767,0.03723142,0.7569348,0.2003545],"study_design_scores_gemma":[0.000002923461,0.00001522084,0.001513672,0.00002965527,0.000001398687,0.00007474185,0.0002972317,0.0001148902,0.0003172101,0.0003498731,0.9972745,0.00000876715],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01665698,0.004219907,0.01347034,0.01041789,0.005878657,0.0006184438,0.007496281,0.003177488,0.938064],"genre_scores_gemma":[0.08318499,0.003710815,0.008602418,0.001362617,0.0008252289,0.000163341,0.003560422,0.000551029,0.8980393],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1232782,"threshold_uncertainty_score":0.4124067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01051566767617922,"score_gpt":0.2718215878051902,"score_spread":0.2613059201290109,"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."}}