{"id":"W4285731499","doi":"10.1111/tgis.12974","title":"Travel mode classification based on <scp>GNSS</scp> trajectories and open geospatial data","year":2022,"lang":"en","type":"article","venue":"Transactions in GIS","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"GNSS applications; Geospatial analysis; Computer science; Robustness (evolution); Discriminative model; Data mining; Global Positioning System; Mode (computer interface); Machine learning; Artificial intelligence; Remote sensing; Geography; 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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001093773,0.00008845343,0.000150407,0.0001699362,0.001421885,0.000131034,0.0006938561,0.00005428559,0.001088833],"category_scores_gemma":[0.0001045838,0.0001026834,0.0000363416,0.0006483484,0.0001847187,0.0003128996,0.00001851923,0.0002591531,0.000005659881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001930194,"about_ca_system_score_gemma":0.0004014928,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06631099,"about_ca_topic_score_gemma":0.1703061,"domain_scores_codex":[0.9983931,0.0004526674,0.0002181845,0.000392493,0.0003606374,0.0001829494],"domain_scores_gemma":[0.9989242,0.0004378345,0.00005717451,0.0004777971,0.0000339058,0.00006906786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002447016,0.005856328,0.01863306,0.0001218064,0.0002607127,0.00001369557,0.2225591,0.3322266,0.001000309,0.02827897,0.004550484,0.3862542],"study_design_scores_gemma":[0.001568178,0.0002121373,0.08189517,0.00002262356,0.0001930289,6.509573e-7,0.09748644,0.7622861,0.000153938,0.002445109,0.05347472,0.0002618679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3410625,0.0001420366,0.5941711,0.012476,0.0008263959,0.002595546,0.002887208,0.0002414124,0.04559777],"genre_scores_gemma":[0.9975739,0.00002969694,0.0003419643,0.0001666976,0.00004329548,0.0001839962,0.0002096371,0.000008843938,0.001442035],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6565113,"threshold_uncertainty_score":0.9998781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08254369428042226,"score_gpt":0.3544979140656704,"score_spread":0.2719542197852481,"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."}}