{"id":"W4205697470","doi":"10.1073/pnas.2111452118","title":"An open repository of real-time COVID-19 indicators","year":2021,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Center for Machine Learning and Health, School of Computer Science, Carnegie Mellon University; Centers for Disease Control and Prevention; Amazon Web Services; National Science Foundation","keywords":"Coronavirus disease 2019 (COVID-19); Social distance; Pandemic; Public health; Internet privacy; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; The Internet; Population; Data science; Computer science; Actuarial science; Medicine; Business; Environmental health; World Wide Web; Nursing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.007837261,0.001720401,0.00174983,0.008467089,0.0009467058,0.007025584,0.003870191,0.002281058,0.04204718],"category_scores_gemma":[0.05202879,0.001071007,0.001430032,0.0120017,0.0006617612,0.004792894,0.005691868,0.003364746,0.04818038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001382589,"about_ca_system_score_gemma":0.005944142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008491383,"about_ca_topic_score_gemma":0.01032339,"domain_scores_codex":[0.9951156,0.0007947318,0.0009929773,0.00106018,0.001760856,0.0002754822],"domain_scores_gemma":[0.9677126,0.009449772,0.003238023,0.009563831,0.007585919,0.002449899],"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":[0.0003835239,0.0001590678,0.01270259,0.001688387,0.000218178,0.0002680208,0.0002696455,0.005068852,0.0009425798,0.008919899,0.8873464,0.08203281],"study_design_scores_gemma":[0.0002598655,0.00007976707,0.01114008,0.0007837893,0.0001151777,0.0002252765,0.0002020641,0.01480494,0.002820604,0.01865342,0.9506514,0.000263509],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001906699,0.0006007492,0.03100915,0.001240892,0.0009220623,0.00027602,0.8897889,0.06331088,0.01094456],"genre_scores_gemma":[0.01245607,0.0007577738,0.03395467,0.0004823217,0.0002634894,0.000505205,0.9390438,0.008264195,0.004272424],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9961298,"threshold_uncertainty_score":0.1406618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04320088745258147,"score_gpt":0.3684871504465092,"score_spread":0.3252862629939277,"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."}}