{"id":"W4386536425","doi":"10.32920/24085086","title":"Redesigning streets for micromobility: improving mobility and access to transportation for less able users","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business","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":[0.0005024442,0.0003675433,0.0001597929,0.0005197996,0.0009548595,0.00133417,0.0004085396,0.000480295,0.00684181],"category_scores_gemma":[0.0009728043,0.0001499945,0.000307325,0.000548968,0.0008623268,0.00135806,0.001107131,0.0003139676,0.0009117541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001229406,"about_ca_system_score_gemma":0.001874769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01757219,"about_ca_topic_score_gemma":0.04752459,"domain_scores_codex":[0.9996997,0.0001491838,0.00001602568,0.00003252378,0.00004392367,0.00005860582],"domain_scores_gemma":[0.9997045,0.00004442927,0.00004480917,0.00005096343,0.00009100111,0.00006417479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002747806,0.0005571097,0.0738574,0.001635946,0.00007995863,0.001107988,0.01763297,0.07276858,0.03268985,0.1749225,0.0319893,0.5924837],"study_design_scores_gemma":[0.0001666604,0.001619132,0.1975508,0.0008549693,0.0002717958,0.001252673,0.03625968,0.05977919,0.02362363,0.05484888,0.6235729,0.0001996806],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7457269,0.001577687,0.1533161,0.004455827,0.0002616623,0.0008498331,0.0009461587,0.0009857437,0.09188006],"genre_scores_gemma":[0.889594,0.001146832,0.0883036,0.0001588879,0.00002417474,0.0002729938,0.0003431005,0.00007726891,0.02007921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01757219,"threshold_uncertainty_score":0.03493983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1365288056091739,"score_gpt":0.3833637582278949,"score_spread":0.2468349526187211,"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."}}