{"id":"W4405236454","doi":"10.1016/j.heliyon.2024.e41101","title":"Enhancing sidewalk accessibility assessment for wheelchair users: An adaptive weighting fuzzy-based approach","year":2024,"lang":"en","type":"article","venue":"Heliyon","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Interdisciplinary Research in Rehabilitation; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Iran National Science Foundation; Université Laval; National Science Foundation","keywords":"Wheelchair; Weighting; Computer science; Transport engineering; Fuzzy logic; Perception; Plan (archaeology); Human–computer interaction; Engineering; Artificial intelligence; World Wide Web; Psychology; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002398958,0.000229161,0.0002936497,0.0001150504,0.0007461854,0.0004771343,0.0004284804,0.0001971381,0.0001540149],"category_scores_gemma":[0.00008782231,0.0002052576,0.000217288,0.0004926127,0.0002014922,0.001231824,0.00002807505,0.0002923072,0.000009557583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003671812,"about_ca_system_score_gemma":0.0009059898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006380165,"about_ca_topic_score_gemma":0.005542828,"domain_scores_codex":[0.9972848,0.0002426598,0.0004581223,0.0008801519,0.0005428704,0.0005914553],"domain_scores_gemma":[0.9987675,0.0003499121,0.0001036094,0.0003750504,0.0001771343,0.0002267792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001276726,0.004746967,0.609488,0.01681263,0.000529266,0.000104013,0.0864678,0.0009619761,0.03106355,0.1201819,0.000738816,0.1276283],"study_design_scores_gemma":[0.006591263,0.003071177,0.5034574,0.00752929,0.001398771,0.000002234672,0.1137314,0.11201,0.07536116,0.09370723,0.07545693,0.007683187],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7924993,0.001610812,0.1807099,0.0005379222,0.0009407903,0.0014267,0.00007452998,0.0007809597,0.02141907],"genre_scores_gemma":[0.9723827,0.00002031172,0.02607883,0.0001471443,0.0007249998,0.00018959,0.00006462295,0.00003225816,0.0003595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1798834,"threshold_uncertainty_score":0.8370161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0479956541192963,"score_gpt":0.3558404539080949,"score_spread":0.3078447997887986,"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."}}