{"id":"W3024259511","doi":"","title":"Joint Modelling of Propensity and Distance for Walking Trip Generation","year":2012,"lang":"en","type":"article","venue":"Transportation Research Board 91st Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"TRIPS architecture; Econometric model; Baseline (sea); Econometrics; Work (physics); Trip generation; Travel behavior; Preferred walking speed; Distance decay; Economics; Transport engineering; Computer science; Engineering; Physical medicine and rehabilitation","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.01631081,0.0003048541,0.0005947924,0.000710279,0.002156908,0.0001686466,0.0004384062,0.0003436037,0.0001405486],"category_scores_gemma":[0.0005154742,0.0003099434,0.0002263095,0.001549572,0.00169313,0.001908719,0.000009940807,0.0009177776,0.000007971444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002094562,"about_ca_system_score_gemma":0.000593941,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0205737,"about_ca_topic_score_gemma":0.03911187,"domain_scores_codex":[0.9915304,0.001185794,0.00129315,0.0008390617,0.003343442,0.001808142],"domain_scores_gemma":[0.9932389,0.0009602798,0.0002997379,0.0004023081,0.004383007,0.0007158279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001428757,0.0008514912,0.803009,0.001508614,0.0001289737,0.00001197829,0.1161462,0.001273193,0.00865576,0.05779166,0.001548517,0.007645918],"study_design_scores_gemma":[0.002584811,0.0005172712,0.9173465,0.0004843867,0.0001245963,9.837012e-8,0.03152742,0.002265079,0.01280836,0.004964536,0.02646289,0.0009140521],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9662485,0.0009896056,0.02714107,0.0009446068,0.000248198,0.002947666,0.0003616468,0.0001168738,0.001001854],"genre_scores_gemma":[0.9913152,0.0005994181,0.005845897,0.00002491042,0.0006372887,0.0004443248,0.0003564875,0.0000604774,0.0007159507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1143375,"threshold_uncertainty_score":0.9999353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2905167700668444,"score_gpt":0.4129203287131816,"score_spread":0.1224035586463372,"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."}}