{"id":"W4293368030","doi":"10.1049/itr2.12250","title":"Evaluation of map‐matching algorithms for smartphone‐based active travel data","year":2022,"lang":"en","type":"article","venue":"IET Intelligent Transport Systems","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Map matching; Computer science; Matching (statistics); Artificial intelligence; Computer vision; Algorithm; Data mining; Pattern recognition (psychology); Global Positioning System; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.01099554,0.0001341724,0.0003255772,0.0001597107,0.0007936097,0.00002643843,0.0007107274,0.00006776586,0.0008891014],"category_scores_gemma":[0.00008321447,0.0001461533,0.0001855673,0.0003909709,0.0001202343,0.0001618378,0.00001609041,0.0001467947,0.000007351617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004309443,"about_ca_system_score_gemma":0.001109162,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02455405,"about_ca_topic_score_gemma":0.01376166,"domain_scores_codex":[0.9959785,0.0008148949,0.0006349449,0.000454646,0.001855501,0.0002614562],"domain_scores_gemma":[0.9981706,0.0003245256,0.0002696952,0.0005784777,0.0005660406,0.00009072597],"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":[0.0004324607,0.00237328,0.003187917,0.0008259711,0.001409857,0.000004863494,0.1934532,0.6249071,0.0008948329,0.009305246,0.001534568,0.1616708],"study_design_scores_gemma":[0.001421642,0.0002833582,0.001719715,0.0001776197,0.002110741,7.861145e-7,0.2471111,0.672893,0.002216884,0.002135143,0.06918765,0.0007423566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1368506,0.001078453,0.8475815,0.000842394,0.002508067,0.004768156,0.004128584,0.000122332,0.002119901],"genre_scores_gemma":[0.9970402,0.00001119988,0.0001456358,0.00003470265,0.0001829031,0.0005167075,0.00174653,0.00001675512,0.0003053609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8601896,"threshold_uncertainty_score":0.9819415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2017619456524844,"score_gpt":0.3928656063924625,"score_spread":0.1911036607399781,"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."}}