{"id":"W4200430233","doi":"10.1109/embc46164.2021.9630022","title":"Impairment Screening Utilizing Biophysical Measurements and Machine Learning Algorithms","year":2021,"lang":"en","type":"article","venue":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Sobriety; Machine learning; Suite; Computer science; Artificial intelligence; Scrutiny; Set (abstract data type); Test (biology); Algorithm; Computer security; Psychology; Psychiatry","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":[0.0003631548,0.0002179429,0.0003586038,0.0001233196,0.00005428657,0.00001906269,0.0002447328,0.0001232836,0.0002713607],"category_scores_gemma":[0.0001841116,0.0001782471,0.0001617553,0.0003949299,0.0001271989,0.00008797069,0.0001022899,0.0005171677,0.000004204944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005758618,"about_ca_system_score_gemma":0.00002361082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001022513,"about_ca_topic_score_gemma":0.0000560236,"domain_scores_codex":[0.998792,0.00006170679,0.0003909427,0.0002615715,0.000248165,0.0002455916],"domain_scores_gemma":[0.9993324,0.0001034706,0.00007518059,0.0001486955,0.0002671011,0.00007317864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003378839,0.0002540927,0.04809175,0.0003716706,0.002716881,0.00001194761,0.006369263,0.1429133,0.7729442,0.0006363765,0.003942784,0.02171404],"study_design_scores_gemma":[0.00215988,0.00009535188,0.01240221,0.001025275,0.0001527724,0.00004086746,0.00216416,0.9550375,0.01389098,0.0001637916,0.01228901,0.0005782446],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9162612,0.001141677,0.07670891,0.002277844,0.002013886,0.0001920679,0.00009665752,0.0001587062,0.001149056],"genre_scores_gemma":[0.9930516,0.0009475096,0.005189601,0.0000899386,0.000251178,0.000012455,0.0001222029,0.00002161982,0.0003138392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8121242,"threshold_uncertainty_score":0.7268707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07038623191291392,"score_gpt":0.2937785537842357,"score_spread":0.2233923218713217,"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."}}