{"id":"W4251694476","doi":"10.32920/ryerson.14664531","title":"Automatic generation of road network data from smartphone GPS trajectories","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Global Positioning System; Computer science; Road map; Mobile mapping; Data mining; Real-time computing; Geography; Cartography; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001527044,0.0002472965,0.000412026,0.00005100812,0.00004127406,0.0001086573,0.0003575427,0.0003570263,0.0008240137],"category_scores_gemma":[0.00003080953,0.0002456895,0.00006781012,0.0001251708,0.00001739856,0.0002118904,0.000331393,0.0003666806,0.00001545191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006024992,"about_ca_system_score_gemma":0.00006614502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008142237,"about_ca_topic_score_gemma":0.0004645486,"domain_scores_codex":[0.9987262,0.00004201223,0.0004671716,0.0003702925,0.0002126402,0.0001817137],"domain_scores_gemma":[0.9986846,0.00004330651,0.0001184971,0.001063337,0.00004950282,0.00004074389],"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":[0.000002931196,0.00006018465,0.0005456918,0.0005153249,0.0006554244,0.00001204296,0.000337142,0.8745573,0.0300754,0.00002417241,0.04875572,0.04445863],"study_design_scores_gemma":[0.00009575268,0.000004729625,0.00960088,0.0002337201,0.0001110496,0.000002144018,0.00004435211,0.9806303,0.008623684,0.00008269665,0.00031551,0.0002551678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.932031,0.002745598,0.05714151,0.00002267302,0.005601948,0.0001753062,0.000156347,0.00119767,0.0009279673],"genre_scores_gemma":[0.9644011,0.0004202022,0.02693767,0.00001008376,0.001387939,0.00001441939,0.006717235,0.00005155342,0.0000598167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.106073,"threshold_uncertainty_score":0.9999995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05342394067863775,"score_gpt":0.2609336855211732,"score_spread":0.2075097448425355,"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."}}