{"id":"W4415258624","doi":"10.1016/j.scs.2025.106906","title":"Who gets to use the street? Evaluate the utilization and inclusiveness using crowdsourced videos and vision-language models","year":2025,"lang":"en","type":"article","venue":"Sustainable Cities and Society","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Pedestrian; Street network; Data collection; Equity (law); Construct (python library); Urban planning; Social equality; Public transport; Sustainable development","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":[0.002938462,0.001041116,0.0006116203,0.002174238,0.0004909997,0.001525451,0.0008597616,0.001141321,0.001543083],"category_scores_gemma":[0.00940014,0.0001727128,0.0007699329,0.001386421,0.0006430749,0.00265662,0.001463967,0.0007124657,0.0006202181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001423735,"about_ca_system_score_gemma":0.0009845382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02606739,"about_ca_topic_score_gemma":0.03368705,"domain_scores_codex":[0.9982559,0.0007051443,0.0001114427,0.0004671882,0.0002831712,0.000177154],"domain_scores_gemma":[0.9967598,0.001741772,0.0003725262,0.0003470599,0.000518149,0.0002606645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001169199,0.001824365,0.53228,0.0015888,0.0006764102,0.0005285526,0.003332775,0.1180422,0.007368676,0.006641714,0.02361908,0.3029282],"study_design_scores_gemma":[0.00006872086,0.0006977547,0.129412,0.0002688599,0.0001963775,0.0001862821,0.006686456,0.8345335,0.007798014,0.009012126,0.01100211,0.0001378519],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9386523,0.000701768,0.03900106,0.001028275,0.0001168803,0.0004596935,0.009547412,0.001034564,0.009458012],"genre_scores_gemma":[0.9677624,0.0001604136,0.02202093,0.0001564266,0.00002359856,0.0001840338,0.008608671,0.00004144579,0.001041946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02606739,"threshold_uncertainty_score":0.05183131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02849238434726745,"score_gpt":0.3472891677411813,"score_spread":0.3187967833939138,"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."}}