{"id":"W4394354430","doi":"10.6084/m9.figshare.12173589","title":"COVID-19-Incidence-data-for-six-high-burdening-countries.csv","year":2020,"lang":"en","type":"dataset","venue":"Figshare","topic":"Healthcare Systems and Public Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Incidence (geometry); Virology; Computer science; Medicine; Mathematics; Outbreak; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.001307527,0.001514653,0.001180691,0.002531718,0.0004339917,0.001608417,0.002414586,0.00182666,0.08247967],"category_scores_gemma":[0.008704946,0.0009800643,0.001888914,0.005878596,0.0003294723,0.001157416,0.001975292,0.001584385,0.0416324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001347481,"about_ca_system_score_gemma":0.00264647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0519396,"about_ca_topic_score_gemma":0.05652907,"domain_scores_codex":[0.9990764,0.0002012352,0.0001582541,0.0002225206,0.0001647171,0.0001768732],"domain_scores_gemma":[0.9968527,0.0008332705,0.0007161181,0.0005618526,0.0006384442,0.0003976014],"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":[0.0001446289,0.00001597241,0.002977901,0.0008780404,0.0001153319,0.00002428993,0.00002280076,0.000504618,0.00006243612,0.0007913894,0.9923746,0.002087994],"study_design_scores_gemma":[0.001468891,0.0000585356,0.02922429,0.001330875,0.0001585159,0.0001814435,0.0001216824,0.001456614,0.0003851622,0.002076322,0.9634632,0.00007447685],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009844759,0.00003092342,0.00004107011,0.00005276968,0.00001560025,0.000008407009,0.9992701,0.0001083427,0.0003742045],"genre_scores_gemma":[0.001049488,0.0000595978,0.0002219132,0.00009133209,0.00001155241,0.00008003616,0.9979813,0.0000648317,0.0004401619],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08247967,"threshold_uncertainty_score":0.275922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1701962509995379,"score_gpt":0.4205022031795547,"score_spread":0.2503059521800167,"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."}}