{"id":"W3197852894","doi":"10.1038/s41598-021-95866-y","title":"Functional data analysis characterizes the shapes of the first COVID-19 epidemic wave in Italy","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Huck Institutes of the Life Sciences; Pennsylvania State University; University of Pennsylvania","keywords":"Coronavirus disease 2019 (COVID-19); Covariate; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Demography; Computer science; Work (physics); Geography; Data science; Statistics; Data mining; Medicine; Machine learning; Virology; Mathematics; Sociology; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.009048876,0.0001667635,0.0005693196,0.0001188418,0.0005764284,0.00008550279,0.0005367923,0.00007600334,0.0007353499],"category_scores_gemma":[0.05607257,0.00008579556,0.0003121724,0.002294491,0.0006699889,0.0001316756,0.00151081,0.0002082699,0.000006771656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001373415,"about_ca_system_score_gemma":0.0003626613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002015223,"about_ca_topic_score_gemma":0.003695063,"domain_scores_codex":[0.9964935,0.0003547585,0.001163875,0.001036006,0.0006471483,0.0003047604],"domain_scores_gemma":[0.9916034,0.00468754,0.0008449677,0.002604752,0.0001790018,0.00008036349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002570359,0.0003997913,0.7762411,0.0003091998,0.001054215,0.0004613617,0.001711533,0.001276308,0.003314896,0.003989767,0.2105676,0.0006485351],"study_design_scores_gemma":[0.0001585441,0.000008289234,0.6356493,0.00005725976,0.000643544,0.0001144044,0.0006672976,0.004017745,0.0005062044,0.2359174,0.1220026,0.0002573123],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.942149,0.0008831953,0.004023418,0.04838951,0.003105217,0.0006513054,0.0001224797,0.00007986968,0.000595974],"genre_scores_gemma":[0.9958894,0.00002403257,0.0004723039,0.001417742,0.00006736119,0.00002808848,0.0001107566,0.000008603271,0.001981742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2319277,"threshold_uncertainty_score":0.9518785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3738848598912662,"score_gpt":0.4087220598206117,"score_spread":0.03483719992934542,"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."}}