{"id":"W6930692127","doi":"10.5281/zenodo.14231533","title":"15min City Score Toolkit – Urban Walkability Analytics","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"","keywords":"Metric (unit); Walkability; Analytics; Flexibility (engineering); 3D city models; Urban planning; Architecture; Plug-in","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0006724688,0.001278379,0.0007497782,0.002057414,0.0004006672,0.001644361,0.001451567,0.0004427265,0.0204469],"category_scores_gemma":[0.00373179,0.0005155759,0.001092633,0.002341229,0.0004039684,0.002026352,0.003139035,0.0009405037,0.00920295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005497097,"about_ca_system_score_gemma":0.001337035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01247897,"about_ca_topic_score_gemma":0.01801838,"domain_scores_codex":[0.99929,0.0001372639,0.0000636978,0.0001576916,0.0002640946,0.00008713966],"domain_scores_gemma":[0.9991444,0.0001985467,0.00009375231,0.0001806865,0.0002814806,0.000101091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005746177,0.0002809222,0.04652853,0.002244528,0.0004557302,0.0004052858,0.002357472,0.09353913,0.006126552,0.03953521,0.5222981,0.2856538],"study_design_scores_gemma":[0.0001410994,0.0001478002,0.03929617,0.0003177559,0.00009452702,0.0003616307,0.00124761,0.5740435,0.01281009,0.05899869,0.3122064,0.0003347559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03252576,0.000282856,0.4486649,0.0003453214,0.0002012779,0.0006443606,0.1469699,0.3465021,0.02386357],"genre_scores_gemma":[0.3343335,0.0005242468,0.3936254,0.0002867063,0.00007539662,0.002379731,0.2222616,0.02975992,0.01675339],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0204469,"threshold_uncertainty_score":0.06840169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0665517121734597,"score_gpt":0.3001618768666537,"score_spread":0.233610164693194,"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."}}