{"id":"W267343212","doi":"","title":"Population Synthesis for Microsimulating Urban Residential Mobility","year":2010,"lang":"en","type":"article","venue":"Transportation Research Board 89th Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Microsimulation; Python (programming language); Population; Computer science; Operations research; Transport engineering; Econometrics; Economics; Engineering","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":[0.001196457,0.0007203556,0.0008234474,0.0007413663,0.0004008166,0.000666032,0.0007898912,0.0008702654,0.005699094],"category_scores_gemma":[0.004914235,0.0004446405,0.001446683,0.0006038253,0.0006435108,0.0008307727,0.001368356,0.0009839719,0.0004296119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001307201,"about_ca_system_score_gemma":0.001111732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01441713,"about_ca_topic_score_gemma":0.008014424,"domain_scores_codex":[0.9997222,0.0001123051,0.00001657344,0.00007215382,0.00004763059,0.00002907717],"domain_scores_gemma":[0.9982522,0.001304444,0.0001375796,0.00008445417,0.0001710922,0.00005018282],"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":[0.000008002945,0.000007679004,0.0003528036,0.00002648098,0.00001414928,0.00001464338,0.00002717639,0.9864689,0.0001531368,0.009811448,0.0001771126,0.002938508],"study_design_scores_gemma":[0.000004132539,0.000007073545,0.00005883284,0.00000527772,0.000005021107,0.000002814367,0.00001180175,0.9937693,0.0001015387,0.005384866,0.000646522,0.000002743468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02035111,0.0001848149,0.9737453,0.0002426648,0.00007132936,0.00008577901,0.0003621678,0.0002592979,0.004697607],"genre_scores_gemma":[0.6156462,0.0006417009,0.3707349,0.0002890883,0.0000958299,0.001251871,0.001383025,0.0002857645,0.009671549],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01441713,"threshold_uncertainty_score":0.02866638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06157314200149411,"score_gpt":0.4240214167168024,"score_spread":0.3624482747153083,"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."}}