{"id":"W3015092349","doi":"10.1038/s41551-020-0534-9","title":"A mountable toilet system for personalized health monitoring via the analysis of excreta","year":2020,"lang":"en","type":"article","venue":"Nature Biomedical Engineering","topic":"Intravenous Infusion Technology and Safety","field":"Engineering","cited_by":169,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Institute of General Medical Sciences; National Cancer Institute; Canary Foundation; National Center for Advancing Translational Sciences; U.S. Department of Health and Human Services","keywords":"Toilet; Fingerprint (computing); Computer science; Biometrics; Workflow; Software; Urinalysis; Cloud computing; Artificial intelligence; Real-time computing; Embedded system; Data mining; Database; Medicine; Urine; Pathology; Operating 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004541204,0.0006524738,0.0007787874,0.0005684876,0.0003521738,0.0008725792,0.001348465,0.001150999,0.005277731],"category_scores_gemma":[0.0009966571,0.0002159568,0.0003134443,0.0003449954,0.0003152914,0.000805411,0.001121044,0.0005596819,0.002757723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002526534,"about_ca_system_score_gemma":0.0003310292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000222751,"about_ca_topic_score_gemma":0.0002726709,"domain_scores_codex":[0.9993507,0.0001166462,0.00002521451,0.0001546535,0.0003148189,0.0000377927],"domain_scores_gemma":[0.999441,0.000160349,0.0001088343,0.0001099042,0.0001343918,0.00004554088],"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":[0.001494468,0.0002572977,0.007802218,0.0004668691,0.0001398755,0.0009331493,0.0002984347,0.002532451,0.7029213,0.002599978,0.02879042,0.2517635],"study_design_scores_gemma":[0.0002174428,0.002308062,0.01357773,0.0001188488,0.000251212,0.005602434,0.0001254329,0.1346581,0.7366594,0.003287586,0.1028991,0.0002945657],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2215026,0.003216968,0.7201723,0.003325011,0.001784536,0.0006091518,0.003213633,0.03109998,0.01507573],"genre_scores_gemma":[0.7823683,0.00122876,0.1757468,0.004009968,0.0008805966,0.0004987114,0.001342107,0.001023165,0.03290151],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005277731,"threshold_uncertainty_score":0.01765573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006044007294189313,"score_gpt":0.224949354240835,"score_spread":0.2189053469466457,"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."}}