{"id":"W4396836029","doi":"10.1016/j.jtrangeo.2024.103896","title":"Measuring exposure and contribution of different types of activity travels to traffic congestion using GPS trajectory data","year":2024,"lang":"en","type":"article","venue":"Journal of Transport Geography","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Chinese University of Hong Kong; National Natural Science Foundation of China","keywords":"Global Positioning System; Trajectory; Transport engineering; Traffic congestion; Computer science; Poison control; Real-time computing; Engineering; Medical emergency; Medicine; 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":[],"consensus_categories":[],"category_scores_codex":[0.001412458,0.00008146418,0.0003053485,0.0003693992,0.0001010041,0.00001976608,0.0001685617,0.00007195136,0.00003376614],"category_scores_gemma":[0.00004825021,0.00007038023,0.0001837524,0.0004202947,0.0001689615,0.0002557476,0.000004366414,0.0001441989,9.122504e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002959914,"about_ca_system_score_gemma":0.0001537048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005428399,"about_ca_topic_score_gemma":0.003230548,"domain_scores_codex":[0.9987842,0.0001429018,0.0003988363,0.0001420375,0.0004159758,0.0001160798],"domain_scores_gemma":[0.9992408,0.0001224547,0.0001786972,0.0001285081,0.0002295255,0.00009998177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009156425,0.00146898,0.5996214,0.001224203,0.002474417,0.00004267207,0.03947362,0.03261791,0.09508649,0.0009041692,0.00002059443,0.2261499],"study_design_scores_gemma":[0.0004104069,0.0002658914,0.9912953,0.0006180782,0.001040168,0.000003052397,0.001075386,0.001269816,0.003353178,0.0001643216,0.0003460555,0.0001582844],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924676,0.001335863,0.005697026,0.0001816762,0.0001301649,0.0001107773,0.00005470467,0.000008744187,0.00001340093],"genre_scores_gemma":[0.9995764,0.0002291655,0.00008917692,0.00000452115,0.00008579882,6.580083e-7,0.000007744739,0.000004485217,0.000002042421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3916739,"threshold_uncertainty_score":0.2870022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04824925752639769,"score_gpt":0.2981744995224144,"score_spread":0.2499252419960167,"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."}}