{"id":"W4318147813","doi":"10.1109/bigdata55660.2022.10021073","title":"Systematic Analysis of Public Transit Data Availability in Canada","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Big Data (Big Data)","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Public transport; Computer science; Transit (satellite); Transport engineering; Data science; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.001427778,0.0001750187,0.000408987,0.0006249642,0.00005286673,0.0000731319,0.006644564,0.00002875797,0.0006091002],"category_scores_gemma":[0.0001870274,0.0001918845,0.00002928183,0.0008616234,0.00003283557,0.000567126,0.00178242,0.0003253357,0.000005477295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004874406,"about_ca_system_score_gemma":0.0004181443,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1152518,"about_ca_topic_score_gemma":0.7952311,"domain_scores_codex":[0.9972154,0.0001775456,0.0007042271,0.0006910281,0.001002942,0.0002087978],"domain_scores_gemma":[0.9954698,0.0001228169,0.0001408295,0.004133263,0.00006147486,0.00007181847],"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":[0.0001136696,0.0008846768,0.007565919,0.00407005,0.009586339,0.0001712657,0.0002847977,0.02784564,0.001182362,0.009257176,0.8237459,0.1152922],"study_design_scores_gemma":[0.0002306109,0.00001416797,0.002196222,0.0001126068,0.0002408723,0.000002211818,0.0004411613,0.9811985,0.0000215716,0.00001619055,0.01533025,0.000195669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.05708959,0.0005162911,0.270536,0.003638291,0.01836656,0.002599537,0.6277262,0.002052311,0.01747524],"genre_scores_gemma":[0.9372232,0.0002110317,0.00009382267,0.0001068096,0.00005233167,0.00005531345,0.06219732,0.00001401938,0.0000461264],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9533528,"threshold_uncertainty_score":0.9987299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2616339857047169,"score_gpt":0.3015119091661445,"score_spread":0.0398779234614276,"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."}}