{"id":"W2104101254","doi":"10.1109/bwcca.2012.72","title":"ABLE Transit: A Mobile Application for Visually Impaired Users to Navigate Public Transit","year":2012,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Leverage (statistics); Popularity; Public transport; Global Positioning System; Mobile device; Schedule; Transit (satellite); World Wide Web; Human–computer interaction; Multimedia; Transport engineering; Telecommunications; Engineering; Artificial intelligence","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":[0.0001848413,0.0005595211,0.0002562912,0.0005219434,0.0002390948,0.0003735897,0.0006182197,0.0006193881,0.01611687],"category_scores_gemma":[0.0009704428,0.0001409918,0.000216982,0.0002569525,0.0001135861,0.0006723531,0.001049077,0.0002727198,0.003544588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001109695,"about_ca_system_score_gemma":0.0001910433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00158205,"about_ca_topic_score_gemma":0.002983666,"domain_scores_codex":[0.9999225,0.00001565092,0.000007628173,0.0000118823,0.00002862575,0.00001376695],"domain_scores_gemma":[0.9997627,0.00009070279,0.00001672426,0.00002728511,0.00005537011,0.00004721796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00237571,0.00110146,0.01300909,0.001382665,0.000148642,0.004013409,0.002322896,0.003047729,0.09586451,0.002807016,0.2566928,0.6172341],"study_design_scores_gemma":[0.001215575,0.003030067,0.06752738,0.0006605509,0.0004934965,0.009914828,0.002139471,0.1193627,0.08093888,0.003998962,0.7102154,0.0005026898],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.2870243,0.001510641,0.3092732,0.001270906,0.0002807276,0.003280657,0.01051991,0.3340887,0.05275102],"genre_scores_gemma":[0.7751307,0.001328645,0.1348698,0.0009029606,0.0001455597,0.001420564,0.01040688,0.003591108,0.07220377],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01611687,"threshold_uncertainty_score":0.05391634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01283255831653369,"score_gpt":0.2461478879114283,"score_spread":0.2333153295948946,"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."}}