{"id":"W4405597648","doi":"10.5198/jtlu.2024.2513","title":"Investigating the impacts of telecommuting on the spatial, temporal, and modal distribution of travel using an agent-based transport simulation model","year":2024,"lang":"en","type":"article","venue":"Journal of Transport and Land Use","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada","keywords":"Telecommuting; Transport engineering; Population; Paratransit; Traffic congestion; Travel behavior; Computer science; Modal; Traffic flow (computer networking); Mode choice; Demand management; Traffic simulation; Microsimulation; Work (physics); Geography; Engineering; Public transport; Computer security; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000944478,0.00008245648,0.000157815,0.00005965473,0.0002444112,0.00003618786,0.00006648244,0.00006332417,0.000004039626],"category_scores_gemma":[0.00003508614,0.00004890139,0.0000639936,0.0001564195,0.0001467991,0.0003151045,6.696925e-7,0.0001582552,1.285816e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001379842,"about_ca_system_score_gemma":0.0001866465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001697589,"about_ca_topic_score_gemma":0.000986357,"domain_scores_codex":[0.999042,0.00007346784,0.0004226645,0.00007795813,0.000283829,0.0001000646],"domain_scores_gemma":[0.999301,0.0002129952,0.0002481597,0.00005669497,0.0001113804,0.00006975031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006104913,0.00003920612,0.2771155,0.0000594123,0.0000246248,0.000003643737,0.01163117,0.7098902,0.0003870879,0.0003437685,0.000002351265,0.0004419402],"study_design_scores_gemma":[0.0003216481,0.0001095471,0.2819438,0.0003769124,0.0001554216,0.000001755187,0.00115107,0.7153476,0.0002974628,0.000179701,0.00003858755,0.00007641982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9264542,0.0001068869,0.07287023,0.0003383713,0.00004421432,0.0001000435,0.0000689841,0.000007301745,0.000009745581],"genre_scores_gemma":[0.9992548,0.00006550534,0.0005449753,0.0000325111,0.0000441516,4.013421e-7,0.00004713101,0.000007331989,0.000003142193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07280063,"threshold_uncertainty_score":0.2566258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06586218497661447,"score_gpt":0.3168825148570754,"score_spread":0.2510203298804609,"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."}}