{"id":"W3015805183","doi":"10.36227/techrxiv.12084168.v1","title":"Smart Shoes For Visually Impaired","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Sight; Visually impaired; Human–computer interaction; Amusement; Computer science; Arduino; Object (grammar); Front (military); ALARM; Architectural engineering; Psychology; Artificial intelligence; Engineering; Social psychology; Electrical engineering; Embedded system","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002744056,0.0002851875,0.0004232751,0.000127395,0.00003560452,0.0001457107,0.0004644261,0.0003040189,0.000135608],"category_scores_gemma":[0.0001202445,0.0002787832,0.0002195852,0.00009281791,0.00001882641,0.00003299184,0.00037157,0.0004433739,0.0002060165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001412123,"about_ca_system_score_gemma":0.00009573685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005253745,"about_ca_topic_score_gemma":0.00004072353,"domain_scores_codex":[0.9985442,0.00003027432,0.0003437118,0.0003892196,0.0002926197,0.0004000178],"domain_scores_gemma":[0.9991018,0.0001601398,0.0000272105,0.0004657405,0.00008440487,0.0001606729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001012842,0.00007188057,0.004788912,0.01617366,0.00183929,0.00005438135,0.001661604,0.03678218,0.0264515,0.002338552,0.897624,0.01211278],"study_design_scores_gemma":[0.0006599855,0.0001156364,0.002630468,0.0003865414,0.00005120123,0.000007643122,0.0001026236,0.7246991,0.01249999,0.001582407,0.2561538,0.001110643],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1812904,0.002308118,0.6065947,0.002820667,0.01521951,0.01142072,0.0005787042,0.01501899,0.1647482],"genre_scores_gemma":[0.9906139,0.0000264947,0.005217037,0.00005144561,0.0009648355,0.0007937718,0.0001240172,0.0001706419,0.002037833],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8093235,"threshold_uncertainty_score":0.9999664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06382850498610941,"score_gpt":0.3184626561165944,"score_spread":0.254634151130485,"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."}}