{"id":"W4379054727","doi":"10.32866/001c.77506","title":"Exploring the X-Minute City by Travel Purpose in Montréal, Canada","year":2023,"lang":"en","type":"article","venue":"Findings","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"TRIPS architecture; Destinations; Context (archaeology); Public transport; Work (physics); Transport engineering; Business; Sustainable transport; Set (abstract data type); Travel behavior; Marketing; Geography; Tourism; Computer science; Sustainability; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0007964548,0.0002236734,0.0002164421,0.001148894,0.005142425,0.003187346,0.0009981813,0.000318055,0.006416896],"category_scores_gemma":[0.002286649,0.0001588711,0.0003219137,0.003134417,0.001836625,0.001419647,0.00185234,0.0007208796,0.0002876017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04077419,"about_ca_system_score_gemma":0.03748639,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9941269,"about_ca_topic_score_gemma":0.9984213,"domain_scores_codex":[0.999302,0.0001599382,0.00001586575,0.000073531,0.0001539443,0.0002947775],"domain_scores_gemma":[0.9986122,0.0001946514,0.0001351202,0.00003897151,0.0006458749,0.0003731663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001906612,0.0001636759,0.6121621,0.0003399604,0.00009165885,0.0008036606,0.2169587,0.002037661,0.001166708,0.05663013,0.03455942,0.07489573],"study_design_scores_gemma":[0.000007573944,0.00004366908,0.6468761,0.0002256,0.00002262715,0.00007941079,0.2745396,0.00136114,0.0001677267,0.001271441,0.07534675,0.00005833113],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.931156,0.0008196794,0.00135114,0.002240882,0.00004225136,0.0001444497,0.002757313,0.00004138892,0.06144688],"genre_scores_gemma":[0.9923645,0.0003258467,0.0007606708,0.0001109489,0.000003800988,0.0000487725,0.0004190288,0.00001603556,0.005950425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04077419,"threshold_uncertainty_score":0.2958388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08041648878885271,"score_gpt":0.2645942263180134,"score_spread":0.1841777375291607,"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."}}