{"id":"W2021599021","doi":"10.1145/1999320.1999342","title":"Road extraction using smart phones GPS","year":2011,"lang":"en","type":"article","venue":"","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Global Positioning System; Computer science; Floating car data; Real-time computing; Focus (optics); Big data; Transport engineering; Data mining; Telecommunications; Engineering; Traffic congestion","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001341032,0.0005982162,0.0005812437,0.002872054,0.0002682298,0.000799402,0.0004161748,0.000445621,0.004990266],"category_scores_gemma":[0.0007505521,0.0002404417,0.0006291809,0.002371225,0.0001222189,0.0006869134,0.0005451641,0.0002186853,0.005208291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002624659,"about_ca_system_score_gemma":0.0003520437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006307314,"about_ca_topic_score_gemma":0.008491508,"domain_scores_codex":[0.9995622,0.00005078381,0.00002187678,0.0001165668,0.0002030072,0.00004542348],"domain_scores_gemma":[0.9996347,0.00006495311,0.00003469072,0.0001094794,0.0001426592,0.00001343531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003934964,0.0001003049,0.03793273,0.0005807126,0.0001977685,0.000664099,0.0004469774,0.04790271,0.1125628,0.002186828,0.01364645,0.7833852],"study_design_scores_gemma":[0.0001628825,0.0004959718,0.2897969,0.0001525721,0.0002961354,0.001499093,0.001379211,0.3635964,0.2206137,0.00569195,0.1160399,0.0002752135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4575301,0.0006439026,0.4669392,0.0002870024,0.0001868465,0.0005419789,0.0258182,0.01505024,0.03300256],"genre_scores_gemma":[0.692708,0.0004738937,0.2834454,0.0000662738,0.0000495968,0.0002038818,0.01480963,0.0003003913,0.007942931],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006307314,"threshold_uncertainty_score":0.01669413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03740388474054059,"score_gpt":0.2439182328899137,"score_spread":0.2065143481493731,"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."}}