{"id":"W3205287033","doi":"","title":"Erratum: Correction: Census Tract Patterns and Contextual Social Determinants of Health Associated With COVID-19 in a Hispanic Population From South Texas: A Spatiotemporal Perspective (JMIR public health and surveillance (2021) 7 8 (e29205))","year":2021,"lang":"en","type":"erratum","venue":"JMIR Public Health and Surveillance","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Census; Census tract; Perspective (graphical); Public health; Coronavirus disease 2019 (COVID-19); Public health surveillance; Geography; Population; Population health; Environmental health; Medicine; Computer science; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009137502,0.0033519,0.003409792,0.006323173,0.004729485,0.005722659,0.005765421,0.01037572,0.09417354],"category_scores_gemma":[0.1192506,0.002462741,0.003987696,0.005295534,0.002154472,0.003118394,0.003512917,0.01576117,0.05361183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006272633,"about_ca_system_score_gemma":0.01627922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1271711,"about_ca_topic_score_gemma":0.124831,"domain_scores_codex":[0.9929538,0.001128587,0.001821573,0.0008703988,0.002430871,0.0007947694],"domain_scores_gemma":[0.9433455,0.01458202,0.00298323,0.003498133,0.03336699,0.002224023],"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":[0.00001017491,0.000003049829,0.00006931218,0.00004974196,0.000006252891,0.0000486766,0.00001028896,0.0000134282,0.000004036423,0.00008745818,0.9986764,0.001021302],"study_design_scores_gemma":[0.0002411106,0.00002988354,0.002743175,0.001749458,0.0001386568,0.0004194048,0.0003146424,0.0004176978,0.000139884,0.001474854,0.9922348,0.00009643279],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0001133766,0.0004592985,0.0003325067,0.06907754,0.9213197,0.00004629187,0.006848516,0.0002774936,0.001525315],"genre_scores_gemma":[0.01343992,0.006372643,0.007261488,0.3501964,0.4004141,0.001459686,0.01948071,0.00274442,0.1986306],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.1271711,"threshold_uncertainty_score":0.3150419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0646615884621939,"score_gpt":0.3627967905650278,"score_spread":0.2981352021028339,"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."}}