{"id":"W3094057148","doi":"10.5260/chara.22.2.43","title":"ProQuest Coronavirus Research Database","year":2020,"lang":"en","type":"article","venue":"The Charleston Advisor","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Coronavirus; Pandemic; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medicine; Disease; Infectious disease (medical specialty)","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":["sts","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002672042,0.0001782645,0.0002519817,0.00006441958,0.002140149,0.00001829583,0.0008884597,0.0001735748,0.002566273],"category_scores_gemma":[0.002249096,0.0001228409,0.00005333263,0.0006177385,0.000377275,0.0001773624,0.0005535493,0.002540511,0.02283287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001901202,"about_ca_system_score_gemma":0.0005894842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003043372,"about_ca_topic_score_gemma":0.001064468,"domain_scores_codex":[0.9951255,0.002070268,0.0006364587,0.0004747279,0.0006844759,0.001008539],"domain_scores_gemma":[0.9963033,0.001757317,0.0001607073,0.0008133582,0.0005217925,0.0004435538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00206956,0.0003808727,0.1099042,0.002564417,0.00007079149,0.000191863,0.1853964,0.00004647649,0.02937705,0.1111684,0.4769279,0.08190217],"study_design_scores_gemma":[0.0003707124,0.0004562964,0.005044937,0.0004929746,0.00002019699,0.000004227506,0.04559463,0.004038378,0.004544647,0.003314137,0.9356888,0.0004300768],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7484707,0.001427074,0.0003044155,0.2259332,0.001334889,0.005365089,0.0002456883,0.0006297004,0.01628921],"genre_scores_gemma":[0.9830723,0.0004129829,0.0001743284,0.01112922,0.001910486,0.000591817,0.00005242236,0.00007275323,0.002583712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4587609,"threshold_uncertainty_score":0.9997607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6790202496771239,"score_gpt":0.6015163348701325,"score_spread":0.07750391480699148,"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."}}