{"id":"W1995320893","doi":"10.1682/jrrd.2005.02.0040","title":"Recognition distance of pedestrian traffic signals by individuals with low vision","year":2006,"lang":"en","type":"article","venue":"The Journal of Rehabilitation Research and Development","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Saint Vincent University","funders":"","keywords":"Icon; Pedestrian; Computer vision; Augmented reality; Light source; Computer science; Artificial intelligence; Optics; Engineering; Transport engineering; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001098153,0.00006530742,0.0001188734,0.0001938214,0.0002298774,0.00004574792,0.0001129945,0.00002517901,0.00004009677],"category_scores_gemma":[0.0005869091,0.00003875683,0.00001960894,0.0002896905,0.0002146802,0.0002653318,0.00001455476,0.0002002026,0.000005698166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005540449,"about_ca_system_score_gemma":0.0001624018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001659975,"about_ca_topic_score_gemma":0.00006034254,"domain_scores_codex":[0.9981704,0.0004410312,0.0004040842,0.0001008136,0.0007148967,0.0001687952],"domain_scores_gemma":[0.9961889,0.003037039,0.0002351211,0.00007950034,0.0003944882,0.00006498957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003269654,0.00277753,0.01495224,0.0003406506,0.00004913554,0.00001891356,0.01475989,0.001527874,0.8330253,0.0001868963,0.02901143,0.1000804],"study_design_scores_gemma":[0.002508872,0.005639839,0.03925621,0.0006689323,0.00001681276,0.0001543334,0.009501443,0.0001190838,0.9079466,0.003267459,0.03065941,0.0002609851],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997626,0.00004820951,0.000504616,0.00145637,0.00002749375,0.0001973424,0.00001076983,0.000004226362,0.0001249598],"genre_scores_gemma":[0.9983926,0.00006339415,0.001359248,0.00002192922,0.00001851528,0.00000527299,0.000002495672,0.000005499418,0.0001310339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09981944,"threshold_uncertainty_score":0.1768055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04233980747670937,"score_gpt":0.3391494131028419,"score_spread":0.2968096056261326,"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."}}