{"id":"W4293196375","doi":"10.2139/ssrn.4119291","title":"A Compact, Low-Cost, and Binary Sensing (BiSense) Platform for Noise-Free and Self-Validated Impedimetric Detection of COVID-19 Infected Patients","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University; University of Calgary","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Binary number; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Noise (video); Virology; Computer science; Physics; Medicine; Artificial intelligence; Mathematics; Internal medicine","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":[0.0005440027,0.0005756258,0.0004638477,0.0007162614,0.0002686383,0.0005764084,0.0007746912,0.001017404,0.001568691],"category_scores_gemma":[0.001034387,0.0003252045,0.0001868527,0.0002331599,0.0003034336,0.0004739726,0.0009025628,0.0006026263,0.000894781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001929545,"about_ca_system_score_gemma":0.0004391615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002096919,"about_ca_topic_score_gemma":0.0005550814,"domain_scores_codex":[0.9992146,0.0001194722,0.00002917313,0.0001206704,0.0004669159,0.00004906147],"domain_scores_gemma":[0.9995753,0.0001001025,0.0001091222,0.00003105015,0.0001225638,0.00006181492],"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":[0.0004224557,0.0002165425,0.001466844,0.0002316105,0.00001872374,0.0002286416,0.00007902093,0.0003607548,0.9527094,0.0005927137,0.001792683,0.04188052],"study_design_scores_gemma":[0.00008724479,0.002455576,0.007422592,0.00004944421,0.00008008773,0.002891108,0.0001218099,0.02663219,0.9480654,0.0005076198,0.01158522,0.0001017051],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6159,0.003073812,0.3635791,0.001527525,0.001147887,0.0009753733,0.001199534,0.003236891,0.00936004],"genre_scores_gemma":[0.8360082,0.000913576,0.1501585,0.001246739,0.0001758164,0.0007531,0.0007231504,0.00008989874,0.009931009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001568691,"threshold_uncertainty_score":0.005247831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00943409292564622,"score_gpt":0.2249517964369228,"score_spread":0.2155177035112765,"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."}}