{"id":"W3013927063","doi":"10.1017/dmp.2020.55","title":"Roadblocks to Infection Prevention Efforts in Health Care: SARS-CoV-2/COVID-19 Response","year":2020,"lang":"en","type":"article","venue":"Disaster Medicine and Public Health Preparedness","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Outbreak; Infection control; Pandemic; Public health; Health care; Personal protective equipment; Medicine; Transmission (telecommunications); Coronavirus disease 2019 (COVID-19); Disease; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medical emergency; Business; Environmental health; Infectious disease (medical specialty); Political science; Intensive care medicine; Nursing; Virology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02319238,0.0008002227,0.0007470858,0.001268637,0.006710862,0.01013733,0.001893146,0.006390288,0.02519755],"category_scores_gemma":[0.04674155,0.0005071699,0.001358596,0.0008913467,0.005827925,0.007562754,0.0136109,0.01796389,0.003900645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007610398,"about_ca_system_score_gemma":0.04157051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01748399,"about_ca_topic_score_gemma":0.02962371,"domain_scores_codex":[0.9850316,0.007875605,0.0007752373,0.0006469066,0.00197063,0.003699975],"domain_scores_gemma":[0.9593944,0.01222484,0.00221032,0.001274803,0.006339365,0.01855632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002445749,0.0009343079,0.02762098,0.002618487,0.0002414776,0.001035259,0.007913255,0.001366371,0.001731197,0.04061176,0.5795127,0.3361697],"study_design_scores_gemma":[0.0002074112,0.001495051,0.08038552,0.009790212,0.0002182866,0.001071875,0.0631033,0.002026934,0.001414267,0.0657915,0.7742112,0.0002844248],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.007839199,0.007456268,0.001175147,0.9698412,0.003632791,0.00005497445,0.0001469815,0.0001264576,0.009726954],"genre_scores_gemma":[0.3528706,0.03631328,0.01181745,0.5814633,0.01082794,0.0003168779,0.0004765286,0.0002354358,0.005678542],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02519755,"threshold_uncertainty_score":0.1226545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2044599814318754,"score_gpt":0.481129717184407,"score_spread":0.2766697357525316,"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."}}