{"id":"W7139674139","doi":"","title":"Leisure Engagement and Travel Demand: Insights for Cultivating Toronto into a Lovable City","year":2025,"lang":"","type":"dissertation","venue":"TSpace (University of Toronto)","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interdependence; Metropolitan area; Urban planning; Work (physics); Population; Urban studies; Census; Spatialization; Social network analysis; Focus (optics)","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":[0.0003426573,0.0002592257,0.0002309973,0.0007460997,0.004297472,0.005173755,0.0005208329,0.0005346712,0.0063017],"category_scores_gemma":[0.001149648,0.0001527446,0.0003236503,0.001841381,0.002986402,0.002281073,0.003211965,0.0008763708,0.0002902428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01467897,"about_ca_system_score_gemma":0.004589805,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3784836,"about_ca_topic_score_gemma":0.6200101,"domain_scores_codex":[0.9996564,0.0001184528,0.0000108807,0.00003410513,0.00004967893,0.000130412],"domain_scores_gemma":[0.9994475,0.0001417464,0.00009269754,0.0000258269,0.0000699611,0.0002222157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001397679,0.0001784305,0.1529597,0.0003859543,0.00004945998,0.001225958,0.6735713,0.002435514,0.002302123,0.1360692,0.005571651,0.02511113],"study_design_scores_gemma":[0.000007450692,0.00005524934,0.1310175,0.0001395988,0.00002651985,0.0001161953,0.8141298,0.002734849,0.0002405628,0.01249823,0.03899908,0.00003495896],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9426948,0.0003531406,0.001287005,0.003437192,0.00001700496,0.0000361304,0.0004073602,0.00001289624,0.05175459],"genre_scores_gemma":[0.9967077,0.0002221491,0.0002929453,0.00005771516,0.00000446399,0.00001272372,0.0001071434,0.00000711915,0.002588088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6215163,"threshold_uncertainty_score":0.7525612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02694500467500464,"score_gpt":0.2976690382169014,"score_spread":0.2707240335418967,"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."}}