{"id":"W4402685925","doi":"10.1016/j.tbs.2024.100905","title":"Unveiling mobility patterns beyond home/work activities: A topic modeling approach using transit smart card and land-use data","year":2024,"lang":"en","type":"article","venue":"Travel Behaviour and Society","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Smart card; Transit (satellite); Work (physics); Land use; Public transport; Transport engineering; Travel behavior; Computer science; Computer security; Business; Data science; Engineering; Civil engineering","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":[0.001392614,0.0001641165,0.0002647453,0.00003637066,0.0007817546,0.0004512246,0.0001828618,0.0001809973,0.00004080076],"category_scores_gemma":[0.0000165499,0.000160253,0.0001473997,0.0002461335,0.0002425763,0.0005008778,0.00005854156,0.000304865,5.083641e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009220197,"about_ca_system_score_gemma":0.0001794384,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02093622,"about_ca_topic_score_gemma":0.002611388,"domain_scores_codex":[0.998394,0.0001768475,0.0002364466,0.0006037205,0.0002888096,0.000300156],"domain_scores_gemma":[0.9992802,0.0001667999,0.00002565499,0.0003444144,0.00003881387,0.0001440863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001838693,0.0003553216,0.6779423,0.0006374842,0.0003361942,0.000008248896,0.3010854,0.002822034,0.0001189656,0.0006816954,0.00008116695,0.01591274],"study_design_scores_gemma":[0.0004429103,0.00002631854,0.0717188,0.0001599624,0.0009295462,0.000003203577,0.1018256,0.8237056,0.00001666515,0.0003811134,0.0001352881,0.0006550074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9172379,0.0005306634,0.08150713,0.0001067382,0.00007690056,0.0002079143,0.0001649786,0.00007155485,0.00009625175],"genre_scores_gemma":[0.9982843,0.0003554352,0.000823562,0.00006487648,0.0001425827,0.00001106059,0.0001221395,0.00001488277,0.000181109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8208836,"threshold_uncertainty_score":0.9855834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09025104478436981,"score_gpt":0.3218988341238349,"score_spread":0.2316477893394651,"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."}}