{"id":"W4381283146","doi":"10.1177/03611981231172503","title":"The Multimodal Accessibility Target (MAT)","year":2023,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Transport engineering; Bus rapid transit; Work (physics); Public transport; Prosperity; Land use; Transportation planning; Multimodal transport; Computer science; Light rail transit; Urban planning; Land-use planning; Business; Engineering; Civil engineering; Economics; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003926235,0.0005294007,0.0005758999,0.002018716,0.0007051555,0.001771663,0.001038046,0.00108306,0.009683546],"category_scores_gemma":[0.01798457,0.0001866364,0.001336493,0.001771854,0.001209204,0.002129655,0.001802201,0.0009565914,0.001215449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002098984,"about_ca_system_score_gemma":0.001338192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00561864,"about_ca_topic_score_gemma":0.00621686,"domain_scores_codex":[0.9969433,0.001261271,0.0002304169,0.0003863689,0.0009468633,0.0002317264],"domain_scores_gemma":[0.9883988,0.004336312,0.002676114,0.0007316397,0.0032183,0.0006388069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001167029,0.0008019977,0.3839822,0.003186324,0.0006145102,0.0004961377,0.005874377,0.01310227,0.007616577,0.08935226,0.02265636,0.47115],"study_design_scores_gemma":[0.0001430958,0.005847372,0.7847708,0.001681911,0.001088032,0.002377288,0.009233245,0.02380689,0.009993443,0.0597174,0.1010394,0.0003012255],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6226888,0.004639765,0.1411576,0.006516288,0.0004815674,0.001549309,0.01077879,0.001248786,0.2109391],"genre_scores_gemma":[0.9816757,0.0004421335,0.01449526,0.0001754804,0.00003248427,0.0007157308,0.0005169883,0.00002596049,0.001920091],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.009683546,"threshold_uncertainty_score":0.03239471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.119053708117924,"score_gpt":0.4482039170453388,"score_spread":0.3291502089274148,"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."}}