{"id":"W4232158084","doi":"10.21203/rs.3.rs-73814/v1","title":"The Impact of COVID-19 on Students' Marks: A Bayesian Hierarchical Modeling Approach","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Thompson Rivers University","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Bayesian probability; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Pandemic; Computer science; Artificial intelligence; Virology; Medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.06734756,0.001046939,0.001894492,0.003262617,0.002556288,0.003293365,0.005814433,0.002262257,0.003709064],"category_scores_gemma":[0.1306631,0.001416186,0.003788604,0.003120566,0.002286726,0.002037811,0.004351514,0.004716686,0.0005107608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00485083,"about_ca_system_score_gemma":0.005727707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1285589,"about_ca_topic_score_gemma":0.09878384,"domain_scores_codex":[0.9480208,0.04210085,0.001215298,0.004516785,0.002828153,0.001318175],"domain_scores_gemma":[0.8310682,0.1444349,0.008473729,0.008057542,0.005692095,0.002273425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001469438,0.001031621,0.4899038,0.0003538736,0.003640935,0.0005561476,0.005463017,0.2636061,0.001054222,0.08692991,0.004735738,0.1412553],"study_design_scores_gemma":[0.00009469065,0.0005108155,0.06155413,0.0001632126,0.0006067447,0.00008159738,0.0007790452,0.9055883,0.000553249,0.02728393,0.002680861,0.0001033808],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4755091,0.0007669862,0.5144716,0.002788158,0.0001504162,0.0008496179,0.001898887,0.0006066831,0.002958461],"genre_scores_gemma":[0.8634586,0.0002192714,0.1317706,0.0002057426,0.00005660393,0.0008031422,0.001230203,0.00006947763,0.002186434],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1285589,"threshold_uncertainty_score":0.3561722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4962134794928291,"score_gpt":0.5809590014724263,"score_spread":0.08474552197959717,"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."}}