{"id":"W3023721945","doi":"10.1371/journal.pcbi.1007893","title":"Calibration of individual-based models to epidemiological data: A systematic review","year":2020,"lang":"en","type":"review","venue":"PLoS Computational Biology","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Vlaamse regering; Fonds Wetenschappelijk Onderzoek","keywords":"Calibration; Measure (data warehouse); Computer science; Population; Goodness of fit; Data mining; Statistics; Econometrics; Medicine; Data science; Machine learning; Mathematics; Environmental health","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03050262,0.002352838,0.007441069,0.01321131,0.00059774,0.004587752,0.003737609,0.002834256,0.005459174],"category_scores_gemma":[0.1664817,0.001789886,0.01071172,0.01196807,0.001090787,0.005207651,0.002216886,0.002074,0.0008688536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005856992,"about_ca_system_score_gemma":0.01525126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008789542,"about_ca_topic_score_gemma":0.01658372,"domain_scores_codex":[0.9801227,0.009383732,0.005694765,0.001316105,0.003206817,0.0002759104],"domain_scores_gemma":[0.8055789,0.1719796,0.0114817,0.002823229,0.007720153,0.0004163088],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001137045,0.00002541154,0.001023732,0.8866677,0.009881479,0.0001122189,0.0002728148,0.001456114,0.0001199956,0.001420051,0.002386112,0.09652068],"study_design_scores_gemma":[0.0001202193,0.0001597805,0.002255474,0.9174331,0.04047365,0.000290639,0.0002813754,0.001028812,0.0002505178,0.002108165,0.03552053,0.00007764789],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0007436159,0.9952803,0.001980806,0.0004769999,0.0001530399,0.0003744921,0.0004740834,0.00003326352,0.0004833089],"genre_scores_gemma":[0.01191135,0.9833566,0.003113132,0.0004818394,0.000101554,0.0005879488,0.0003213955,0.00002253269,0.0001035514],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9694974,"threshold_uncertainty_score":0.1613152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7137189189898845,"score_gpt":0.5131527409126169,"score_spread":0.2005661780772676,"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."}}