{"id":"W4363677222","doi":"10.36227/techrxiv.22337803","title":"A Wearable RFID-Based Navigation System for the Visually Impaired","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Navigation system; Wearable computer; Computer science; Human–computer interaction; Orientation (vector space); Set (abstract data type); Simple (philosophy); Visually impaired; Wearable technology; Identification (biology); Embedded system; Computer vision; 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":[0.000201825,0.0003707807,0.0003345413,0.0002933773,0.0002631487,0.000339985,0.0005546137,0.0005775316,0.002695994],"category_scores_gemma":[0.0003038803,0.0001539762,0.0002942611,0.000236789,0.0001606319,0.0005639177,0.0005493663,0.0002020726,0.001260045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001353508,"about_ca_system_score_gemma":0.0002774979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000570113,"about_ca_topic_score_gemma":0.0008291273,"domain_scores_codex":[0.9998902,0.000018487,0.00001024127,0.00003576544,0.00003140765,0.000013944],"domain_scores_gemma":[0.9998562,0.00001663762,0.00001806128,0.00002718874,0.00006255024,0.00001917709],"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":[0.0006795304,0.0001761134,0.002609106,0.0006395706,0.00006452519,0.0008830973,0.0003760403,0.0007765152,0.6440237,0.001134673,0.004959927,0.3436773],"study_design_scores_gemma":[0.0004520896,0.01070509,0.06632268,0.0005542257,0.0009737703,0.02111628,0.000965892,0.06643039,0.6796364,0.002621818,0.1497367,0.000484725],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4088862,0.004990753,0.5664716,0.0005242328,0.0007604007,0.0003123742,0.0007043061,0.006393956,0.0109561],"genre_scores_gemma":[0.7792054,0.001583157,0.1996365,0.0004906184,0.00009354905,0.0001858881,0.0003892111,0.00009804398,0.01831762],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002695994,"threshold_uncertainty_score":0.009019017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1099923912485105,"score_gpt":0.349819237307981,"score_spread":0.2398268460594706,"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."}}