{"id":"W4321763682","doi":"10.15353/acmla.n171.5027","title":"Transit Vector Data","year":2023,"lang":"en","type":"article","venue":"Bulletin - Association of Canadian Map Libraries and Archives (ACMLA)","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Transit (satellite); Computer science; Agency (philosophy); Public transport; File format; World Wide Web; Database; Data science; Information retrieval; Transport engineering; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00009233018,0.00009586041,0.0001334556,0.0004393266,0.00009779719,0.00007271141,0.000234167,0.00005530484,0.0001200255],"category_scores_gemma":[0.00003058024,0.0001096912,0.00002830699,0.0002317049,0.00003680827,0.0001145306,0.00005679677,0.000093711,0.00002496728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001249435,"about_ca_system_score_gemma":0.00003207033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006512657,"about_ca_topic_score_gemma":0.001919338,"domain_scores_codex":[0.9993132,0.00002531388,0.0001683306,0.0001476417,0.0001078938,0.0002376252],"domain_scores_gemma":[0.9994876,0.0001148428,0.00003709837,0.0002120045,0.000004210442,0.0001442864],"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":[0.000004390452,0.000003802301,0.0008966132,0.00008309478,0.00007851674,0.000004138293,0.0004334939,0.0001426825,0.0001059621,0.0219096,0.9641526,0.01218508],"study_design_scores_gemma":[0.0001589928,0.00001296367,0.02105464,0.00002436517,0.0000150043,2.559501e-7,0.0001412817,0.007855796,0.0001015153,0.000460789,0.9700626,0.000111822],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02641925,0.003100596,0.01862738,0.2540829,0.003899272,0.002337432,0.008776346,0.0236246,0.6591323],"genre_scores_gemma":[0.9825574,0.002693053,0.003686307,0.0005878233,0.0002214673,0.00002649072,0.001051917,0.00005847903,0.009117065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9561381,"threshold_uncertainty_score":0.4473079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01261536091946526,"score_gpt":0.1760768012178911,"score_spread":0.1634614402984258,"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."}}