{"id":"W4296100806","doi":"10.3390/s22186747","title":"Automated Fluid Intake Detection Using RGB Videos","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"Thermoregulation and physiological responses","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research","keywords":"Convolutional neural network; Artificial intelligence; Deep learning; Computer science; RGB color model; Machine learning; Artificial neural network; Computer vision","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001740711,0.0006484356,0.0003502846,0.0007954899,0.0001165189,0.0003613645,0.000319654,0.0004346858,0.001820119],"category_scores_gemma":[0.000663679,0.0001826731,0.0003219748,0.0003719759,0.0001093869,0.0003486122,0.0003559328,0.0002255881,0.0006305391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00026459,"about_ca_system_score_gemma":0.0003141659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006634724,"about_ca_topic_score_gemma":0.009678216,"domain_scores_codex":[0.9998487,0.00001899812,0.000006622699,0.00004870484,0.00004664108,0.00003027234],"domain_scores_gemma":[0.9998784,0.00002108284,0.0000205548,0.00000835359,0.0000595405,0.00001202923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001617064,0.0004405993,0.04704862,0.0006909469,0.000203201,0.0006816005,0.0001859582,0.02233853,0.2420866,0.0006325167,0.01329731,0.6707771],"study_design_scores_gemma":[0.00007578866,0.0007426316,0.1786313,0.0002479714,0.0001551894,0.001042532,0.0004011297,0.63965,0.1633707,0.001530759,0.01405624,0.00009571607],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6981987,0.002968121,0.275493,0.0004622209,0.000348445,0.0003806758,0.007529572,0.004310657,0.01030856],"genre_scores_gemma":[0.9107758,0.001258298,0.07937808,0.0002362701,0.00008229781,0.0001529898,0.003381742,0.0001033121,0.004631129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006634724,"threshold_uncertainty_score":0.01319218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03897706704868793,"score_gpt":0.3095041609326323,"score_spread":0.2705270938839444,"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."}}