{"id":"W3015633724","doi":"10.1007/s11067-021-09542-9","title":"Routine Pattern Discovery and Anomaly Detection in Individual Travel Behavior","year":2021,"lang":"en","type":"article","venue":"Networks and Spatial Economics","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Latent Dirichlet allocation; Anomaly detection; Probabilistic logic; Statistical model; Travel behavior; Trajectory; Generative model; Key (lock); Data modeling","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003471942,0.00006758975,0.000142362,0.00003736403,0.0002169779,0.0002017738,0.0000441593,0.0001012423,0.00005261692],"category_scores_gemma":[0.00001893011,0.00007775755,0.00003234764,0.00007278287,0.0001022899,0.0001617242,0.00002756723,0.0001069372,6.830875e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004705952,"about_ca_system_score_gemma":0.00007166228,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0360101,"about_ca_topic_score_gemma":0.679108,"domain_scores_codex":[0.9993236,0.00008799586,0.0001844409,0.0002147882,0.0000393941,0.0001497491],"domain_scores_gemma":[0.999727,0.00006730484,0.00005150469,0.00007517554,0.00001789158,0.00006115771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00000758378,0.0000564186,0.3654148,0.000003746765,0.00001411445,0.000003453194,0.002055751,0.002136452,0.000004355324,0.0002965509,0.000002226269,0.6300045],"study_design_scores_gemma":[0.0003987241,0.00003150808,0.9069158,0.000009325936,0.00005737156,0.000001121959,0.002187865,0.08962114,0.00003425546,0.00021099,0.0003672103,0.0001647132],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815586,0.0001489024,0.01761902,0.0002120529,0.0001074077,0.00008047997,0.000009894014,0.000006303461,0.0002573849],"genre_scores_gemma":[0.9988744,0.0005447107,0.000009148617,0.0001493849,0.0002925794,0.00001315314,0.00002867423,0.000004891369,0.00008304389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6430979,"threshold_uncertainty_score":0.9704092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01519312659386688,"score_gpt":0.2447698876219552,"score_spread":0.2295767610280884,"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."}}