{"id":"W2793361901","doi":"10.1111/grow.12243","title":"Generational Differences in Trip Timing and Purpose: Evidence from Canada","year":2018,"lang":"en","type":"article","venue":"Growth and Change","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Baby boomers; TRIPS architecture; Descriptive statistics; Demographic economics; General Social Survey; Population; License; Demography; Travel behavior; Demographics; Generation x; Geography; Psychology; Economics; Statistics; Sociology; Social psychology; Political science; Transport engineering","routes":{"ca_aff":false,"ca_fund":true,"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":[0.00219628,0.0002846096,0.0003438422,0.00219559,0.002354733,0.00144056,0.001273248,0.0003684762,0.002640786],"category_scores_gemma":[0.008458822,0.0003105901,0.0009038028,0.004563141,0.001036075,0.0004312361,0.001444964,0.000584928,0.0001607661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006726327,"about_ca_system_score_gemma":0.01283769,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9810309,"about_ca_topic_score_gemma":0.9881594,"domain_scores_codex":[0.9984219,0.0002683235,0.0001022797,0.0002815857,0.0005084733,0.0004175321],"domain_scores_gemma":[0.9905095,0.001420165,0.002069558,0.0007487492,0.004245531,0.001006578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001016496,0.00001523105,0.9908737,0.00004642222,0.0001291412,0.00009670627,0.002329969,0.0001216983,0.00006374733,0.0003381602,0.0006356167,0.005247905],"study_design_scores_gemma":[0.0000037258,0.00001181405,0.9970707,0.00005587567,0.00003785514,0.00003390621,0.00181302,0.0001029396,0.00003468241,0.00005063515,0.0007761158,0.000008736217],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886383,0.00191673,0.0002887008,0.0003601612,0.00002724104,0.00004339759,0.003777571,0.000008244825,0.004939671],"genre_scores_gemma":[0.9967172,0.001217269,0.0001671117,0.00004723079,0.000004416268,0.00001153597,0.001279,0.000007102711,0.0005492143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01896906,"threshold_uncertainty_score":0.04880315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1084096385674581,"score_gpt":0.2894390483559528,"score_spread":0.1810294097884947,"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."}}