{"id":"W4317347026","doi":"10.2196/42895","title":"Multidimensional Machine Learning for Assessing Parameters Associated With COVID-19 in Vietnam: Validation Study","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"COVID-19 Clinical Research Studies","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Asymptomatic; Cutoff; Medicine; Internal medicine; Correlation; Relative risk; Population; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Confidence interval; Mathematics; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003554147,0.0006292429,0.0003753711,0.0008562253,0.0003577682,0.0004567667,0.000374087,0.0003365905,0.0009520289],"category_scores_gemma":[0.005082691,0.0001873489,0.0008046704,0.0006894157,0.0004790926,0.0003481154,0.000607007,0.0005650295,0.0002344486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006792211,"about_ca_system_score_gemma":0.00101422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008319334,"about_ca_topic_score_gemma":0.004210857,"domain_scores_codex":[0.9989179,0.0006366167,0.00007393722,0.0001689774,0.0001031943,0.00009931083],"domain_scores_gemma":[0.9970717,0.001298392,0.0005432015,0.0003792271,0.000446112,0.0002613772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002687002,0.0002219956,0.9928202,0.00001579245,0.00009286572,0.00006452669,0.0001951852,0.001013834,0.0003071771,0.00004840935,0.0001344826,0.004816885],"study_design_scores_gemma":[0.00005450858,0.001401906,0.9707704,0.00002296555,0.0001099514,0.0003293109,0.001030599,0.02499199,0.0006786042,0.0001508841,0.0004405139,0.00001822783],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989635,0.000036962,0.0005972622,0.00001379775,0.000002615613,0.00003195242,0.0001850553,0.000004631594,0.0001643094],"genre_scores_gemma":[0.9987689,0.00003076537,0.0005774234,0.000006290963,0.000002575805,0.00003307423,0.0004894455,0.000002108423,0.00008925922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008319334,"threshold_uncertainty_score":0.01879638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2326966723334393,"score_gpt":0.5633061151840487,"score_spread":0.3306094428506094,"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."}}