{"id":"W3114724032","doi":"10.3934/fods.2021001","title":"An international initiative of predicting the SARS-CoV-2 pandemic using ensemble data assimilation","year":2020,"lang":"en","type":"article","venue":"Foundations of Data Science","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Office of Naval Research; Agencia Nacional de Promoción Científica y Tecnológica; National Centre for Earth Observation; Natural Environment Research Council; Sight Research UK","keywords":"Coronavirus disease 2019 (COVID-19); Data assimilation; Term (time); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Pandemic; Computer science; Econometrics; Geography; Statistics; Mathematics; Meteorology; Medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003847145,0.0006481116,0.0005665022,0.0006307894,0.0003685046,0.0008914036,0.0006748693,0.0006756886,0.001376765],"category_scores_gemma":[0.004115394,0.0001697057,0.0007533564,0.0006829196,0.0002066058,0.001116552,0.001236054,0.001472055,0.0004572081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003711729,"about_ca_system_score_gemma":0.001379177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01124101,"about_ca_topic_score_gemma":0.007222759,"domain_scores_codex":[0.9994959,0.0002214758,0.00002293407,0.000112122,0.0001038297,0.00004383855],"domain_scores_gemma":[0.9983953,0.0004505403,0.00008923085,0.0003920269,0.0005128978,0.000159995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004373556,0.0004149805,0.04901183,0.0001188373,0.0005195193,0.000179261,0.000259582,0.5518793,0.0100788,0.02060426,0.02357825,0.3429179],"study_design_scores_gemma":[0.00001894021,0.0001130745,0.006739968,0.00001388387,0.00003916432,0.00002455861,0.00005421872,0.9799381,0.002039319,0.004987889,0.006010426,0.00002046944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2850344,0.001415376,0.6783671,0.006529674,0.001344304,0.0002469537,0.005469078,0.003103037,0.01849004],"genre_scores_gemma":[0.6789424,0.0008054582,0.3038833,0.0004415816,0.0003779205,0.0001547205,0.008429448,0.0003111484,0.006654013],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01124101,"threshold_uncertainty_score":0.02235121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8207606729586456,"score_gpt":0.57113521935207,"score_spread":0.2496254536065756,"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."}}