{"id":"W2162487117","doi":"10.1007/s11116-008-9166-8","title":"Modelling daily activity program generation considering within-day and day-to-day dynamics in activity-travel behaviour","year":2008,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":89,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Canadian Natural Resources; University of Alberta","funders":"Social Sciences and Humanities Research Council of Canada; Transport Canada; McLean Foundation","keywords":"Duration (music); Scheduling (production processes); Econometric model; Set (abstract data type); Econometrics; Computer science; Operations research; Simulation; Mathematics; Engineering; Operations management","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000636076,0.00068656,0.001034569,0.0004839425,0.0003590008,0.001017898,0.001287575,0.001416355,0.002869851],"category_scores_gemma":[0.002134783,0.0009135681,0.001039382,0.0009512124,0.0005370442,0.001135412,0.0005496607,0.000878403,0.0002932171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001227984,"about_ca_system_score_gemma":0.001204165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04432405,"about_ca_topic_score_gemma":0.03385845,"domain_scores_codex":[0.9996676,0.000112981,0.00001325248,0.0001013143,0.00003152946,0.00007323236],"domain_scores_gemma":[0.9988942,0.0008143368,0.00008132342,0.0000388925,0.00009406274,0.00007728149],"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":[0.00001966171,0.00002444047,0.000733101,0.000007474888,0.00001485607,0.0000176039,0.00001369171,0.9970303,0.0001096498,0.0005723807,0.00007056193,0.001386216],"study_design_scores_gemma":[0.000002039806,0.000005209682,0.0002426003,5.066543e-7,0.00000328917,0.000002191891,0.000004726094,0.9994086,0.00002488474,0.0002738344,0.00003074696,0.000001314982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7120453,0.000282439,0.2793254,0.0004155068,0.00008200218,0.0001190977,0.001007689,0.0003414927,0.006381012],"genre_scores_gemma":[0.9871892,0.00007815746,0.008106407,0.00001842198,0.00001325734,0.00007805041,0.0003148127,0.00004051183,0.004161115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04432405,"threshold_uncertainty_score":0.08813208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04801424598588602,"score_gpt":0.2936223921541173,"score_spread":0.2456081461682313,"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."}}