{"id":"W3040141037","doi":"10.15353/acmla.n164.1730","title":"2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository","year":2020,"lang":"en","type":"article","venue":"Bulletin - Association of Canadian Map Libraries and Archives (ACMLA)","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Context (archaeology); Coronavirus; Coronavirus Infections; Virology; Computer science; Library science; Data science; Geography; Medicine; Outbreak; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.009787499,0.0008029137,0.001666332,0.02133429,0.002581717,0.004763062,0.0039813,0.001350292,0.03055991],"category_scores_gemma":[0.04278646,0.0006767397,0.001458867,0.02927439,0.0009440126,0.003098346,0.004156343,0.002135179,0.01539809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01015219,"about_ca_system_score_gemma":0.05958875,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.516583,"about_ca_topic_score_gemma":0.5694923,"domain_scores_codex":[0.9928222,0.0009641699,0.001281613,0.0005685212,0.003659122,0.0007043604],"domain_scores_gemma":[0.9418101,0.007549779,0.004217223,0.004796794,0.03753328,0.004092909],"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":[0.0002857865,0.00003162969,0.01117139,0.006492504,0.0001870079,0.0002348889,0.0006170064,0.0003386473,0.0007263965,0.008012468,0.8951654,0.07673683],"study_design_scores_gemma":[0.00001962839,0.00001111811,0.01030551,0.002763504,0.00008311037,0.00007914007,0.0002886914,0.0001011362,0.0003698425,0.0009040619,0.9850233,0.00005092761],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001560465,0.006838305,0.002380337,0.002930117,0.0005955549,0.0004424914,0.9655861,0.001462475,0.01820417],"genre_scores_gemma":[0.005569681,0.007271507,0.007992268,0.001071004,0.0001604102,0.0004577343,0.9726795,0.0004236593,0.004374186],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.516583,"threshold_uncertainty_score":0.9725279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2090479415180505,"score_gpt":0.3384281560139691,"score_spread":0.1293802144959186,"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."}}