{"id":"W4381190033","doi":"10.1007/s11538-023-01174-z","title":"SPADE4: Sparsity and Delay Embedding Based Forecasting of Epidemics","year":2023,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Embedding; Computer science; Variable (mathematics); Population; Observable; Trajectory; Scarcity; Regression; Artificial intelligence; Machine learning; Mathematics; Statistics; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002094061,0.0008370067,0.001380382,0.001238214,0.0004806432,0.001004533,0.001751033,0.001646106,0.002861001],"category_scores_gemma":[0.01360178,0.0006287828,0.0009246832,0.0008802561,0.0006172039,0.002070283,0.001470429,0.002310241,0.0005428298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009147653,"about_ca_system_score_gemma":0.001510292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00714358,"about_ca_topic_score_gemma":0.00756406,"domain_scores_codex":[0.9995696,0.0001648829,0.00002810663,0.000100704,0.00007812477,0.00005847833],"domain_scores_gemma":[0.9941878,0.004255045,0.0002550955,0.0005070054,0.0005880839,0.0002069851],"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":[0.000230451,0.00008088821,0.002522687,0.00008417591,0.00008400686,0.00006987492,0.00005729972,0.9287015,0.0008539144,0.01454864,0.005458117,0.04730838],"study_design_scores_gemma":[0.000004811689,0.000007118645,0.00005971958,0.000002348812,0.000002654131,0.000004837565,0.000002455508,0.9959196,0.0001161932,0.003717737,0.0001602125,0.00000222348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09967685,0.0009208999,0.8921546,0.001464985,0.0003564553,0.00008200012,0.001802495,0.001697734,0.001843989],"genre_scores_gemma":[0.7674291,0.0007565899,0.22053,0.000285189,0.0003831175,0.0002184849,0.004272634,0.0002495194,0.005875547],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00714358,"threshold_uncertainty_score":0.01420403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02799922686486235,"score_gpt":0.2642633566019269,"score_spread":0.2362641297370646,"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."}}