{"id":"W4386159878","doi":"10.1109/icarm58088.2023.10218843","title":"Blind Lane Detection and Following for Assistive Navigation of Vision Impaired People","year":2023,"lang":"en","type":"article","venue":"","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Robustness (evolution); Artificial intelligence; Computer vision; Object detection; Convolutional neural network; Wearable computer; Visually impaired; Task (project management); Human–computer interaction; Pattern recognition (psychology); Embedded system; Engineering","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":[0.0001535942,0.0003483858,0.0002135521,0.0003514262,0.0002122083,0.0002686416,0.0003606633,0.0004434368,0.00120813],"category_scores_gemma":[0.0005802352,0.0001351803,0.0001934262,0.0001382007,0.0001499836,0.0003506518,0.0004337954,0.0002068187,0.0003658021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001203256,"about_ca_system_score_gemma":0.0003368788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001975833,"about_ca_topic_score_gemma":0.003637901,"domain_scores_codex":[0.9999388,0.00001183636,0.000003862347,0.00001768518,0.00001613182,0.00001168119],"domain_scores_gemma":[0.999862,0.00003157729,0.00002060012,0.00001332372,0.00005043622,0.00002212386],"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":[0.0007454513,0.0002641656,0.01219964,0.0003670967,0.00006096,0.0009034476,0.0004879876,0.008275079,0.2068994,0.0006056287,0.00390278,0.7652884],"study_design_scores_gemma":[0.0001547791,0.001936135,0.1063392,0.0002986304,0.000346332,0.007397258,0.0009876381,0.6626837,0.1941051,0.008382595,0.01715394,0.0002146808],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5421306,0.002054892,0.4473234,0.000331079,0.0001673036,0.000104094,0.0002893356,0.003288646,0.004310627],"genre_scores_gemma":[0.9342044,0.0005284673,0.06275357,0.0000911205,0.00002135925,0.00004123166,0.0001118341,0.0000289345,0.002219027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001975833,"threshold_uncertainty_score":0.004041612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04083809709745802,"score_gpt":0.3342513891802948,"score_spread":0.2934132920828368,"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."}}