{"id":"W3214340438","doi":"10.32920/ryerson.14664189.v1","title":"Automatic generation of road network data from taxi GPS trajectories","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Taxis; Global Positioning System; Beijing; Transport engineering; Computer science; Field (mathematics); Floating car data; Geography; Engineering; Telecommunications; Traffic congestion","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001422275,0.0002357589,0.0003795395,0.00004809686,0.00003969788,0.0001126384,0.0003715748,0.0003547016,0.000751689],"category_scores_gemma":[0.00003332013,0.0002330094,0.00006582125,0.0001203661,0.00001572018,0.0002146905,0.00032025,0.0003597713,0.00001223239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000565808,"about_ca_system_score_gemma":0.00006299442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007257843,"about_ca_topic_score_gemma":0.000424206,"domain_scores_codex":[0.9987856,0.00004001593,0.0004399309,0.0003569174,0.0002052318,0.0001722787],"domain_scores_gemma":[0.998733,0.0000394204,0.0001205994,0.001022395,0.00004695038,0.00003758284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001670956,0.00003924134,0.0002351642,0.0004127976,0.0004846312,0.000009113667,0.0002793981,0.8968146,0.01938653,0.00004365803,0.04828523,0.03400793],"study_design_scores_gemma":[0.00007317994,0.000004310099,0.003821534,0.0002262516,0.0001030064,0.000001948269,0.00005166583,0.9888377,0.006041353,0.00009923804,0.0004991312,0.0002407407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9078317,0.003040124,0.08067095,0.00002556041,0.005437973,0.0002093067,0.0001952727,0.001371636,0.001217453],"genre_scores_gemma":[0.9639953,0.0003677388,0.02835516,0.000009540804,0.001343869,0.00001458468,0.005793985,0.0000491282,0.00007065653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09202301,"threshold_uncertainty_score":0.9501848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0569027634516439,"score_gpt":0.2658423474591411,"score_spread":0.2089395840074972,"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."}}