{"id":"W3093657035","doi":"10.7717/peerj.10261","title":"Computerized monitoring of COVID-19 trials, studies and registries in ClinicalTrials.gov registry","year":2020,"lang":"en","type":"article","venue":"PeerJ","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine; National Institutes of Health; Lister Hill National Center for Biomedical Communications","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medicine; Clinical trial; Betacoronavirus; MEDLINE; Intensive care medicine; Virology; Internal medicine; Outbreak; Infectious disease (medical specialty); Biology; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1641934,0.001379702,0.003659827,0.05938704,0.001235826,0.009133039,0.002950378,0.001841342,0.0147329],"category_scores_gemma":[0.3383092,0.001895889,0.002227999,0.06666932,0.001143974,0.007665287,0.005203463,0.002976243,0.005292822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003565383,"about_ca_system_score_gemma":0.01621646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00291261,"about_ca_topic_score_gemma":0.003561674,"domain_scores_codex":[0.827087,0.06855022,0.06910062,0.01186175,0.02146671,0.001933747],"domain_scores_gemma":[0.3356727,0.4227679,0.1407104,0.05294853,0.04092856,0.006971932],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00629646,0.0006513536,0.2708764,0.02196124,0.002829417,0.000883487,0.003591407,0.007406251,0.002789507,0.02862659,0.1707679,0.4833201],"study_design_scores_gemma":[0.004354957,0.001465816,0.2460567,0.01002179,0.003349418,0.001895824,0.001894773,0.0214603,0.008115214,0.03310832,0.6675859,0.0006910468],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.08953563,0.01388603,0.1452882,0.008306183,0.00117513,0.03840475,0.6272539,0.02259026,0.05355976],"genre_scores_gemma":[0.1906385,0.005546148,0.4040448,0.002696295,0.001342099,0.05187577,0.3353168,0.002842996,0.005696526],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8358066,"threshold_uncertainty_score":0.8683482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3952706632404356,"score_gpt":0.4982625845876131,"score_spread":0.1029919213471775,"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."}}