{"id":"W3164547741","doi":"10.82308/21404","title":"The use of Bluetooth and smartphone GPS data to investigate factors associated to variations of travel times and delays","year":2017,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Global Positioning System; Bluetooth; Computer science; Internet privacy; Telecommunications; Wireless","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008933404,0.0004293316,0.00026109,0.002013229,0.0002907643,0.001111852,0.0003645664,0.000349351,0.001339379],"category_scores_gemma":[0.005820467,0.0002336762,0.000523583,0.003190835,0.0001929486,0.0004375608,0.0004553094,0.0004074237,0.0003871488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000866814,"about_ca_system_score_gemma":0.001871499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2029787,"about_ca_topic_score_gemma":0.2772977,"domain_scores_codex":[0.9993314,0.0001710553,0.0000438663,0.0001432529,0.0002270149,0.00008349733],"domain_scores_gemma":[0.996857,0.001302583,0.0005231489,0.0002093699,0.0009802697,0.000127633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002369304,0.0000747642,0.9259166,0.0002650541,0.0003587786,0.0001895872,0.001970412,0.006006015,0.00248684,0.00046827,0.001474828,0.06055188],"study_design_scores_gemma":[0.00001372935,0.0002306586,0.9741399,0.0000808761,0.0002116745,0.0001915454,0.00282367,0.01405874,0.001569979,0.0002196011,0.006417181,0.00004248443],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810445,0.0006503291,0.007594839,0.0002731198,0.00005643079,0.0001152965,0.005574793,0.0001239777,0.00456679],"genre_scores_gemma":[0.987306,0.0006263192,0.006434642,0.00004480067,0.00002810702,0.00009698323,0.002479814,0.00002376083,0.002959601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2029787,"threshold_uncertainty_score":0.4035946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1234383612261668,"score_gpt":0.2982792326508436,"score_spread":0.1748408714246767,"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."}}