{"id":"W4319350099","doi":"10.2174/2215083809666230207142240","title":"COVID-19: Impact, Diagnosis, Management and Phytoremediation","year":2023,"lang":"en","type":"article","venue":"Current Traditional Medicine","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Pandemic; China; Coronavirus disease 2019 (COVID-19); Population; Economic growth; Health care; Business; Development economics; Political science; Medicine; Environmental health; Economics; Disease","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004911725,0.0002013684,0.0003003151,0.0005968267,0.0001395297,0.00001375412,0.0001048999,0.00005712989,0.0002611962],"category_scores_gemma":[0.0007636338,0.0001529322,0.00008421909,0.0007964317,0.0002743446,0.00009730481,0.00004463262,0.0002600358,0.0001668053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003483354,"about_ca_system_score_gemma":0.000289212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002160508,"about_ca_topic_score_gemma":0.000003739908,"domain_scores_codex":[0.9979098,0.00004719542,0.0003033505,0.0003933469,0.0009832911,0.0003630175],"domain_scores_gemma":[0.9988357,0.0004291332,0.00006068788,0.0002239082,0.0000845297,0.0003660615],"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":[0.0003633143,0.0005815609,0.1971592,0.002033371,0.0002859395,0.0004432618,0.0007962409,0.000002837593,0.001394138,0.009276272,0.7243706,0.06329327],"study_design_scores_gemma":[0.005182046,0.0006169829,0.4121886,0.000435014,0.0001651253,0.00009266783,0.0002106935,0.0005688601,0.0004429679,0.008370394,0.5715175,0.0002091542],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9375637,0.01114886,0.001059707,0.0394956,0.002470773,0.002259171,0.0002505334,0.0007631658,0.004988461],"genre_scores_gemma":[0.9502991,0.001428066,0.00004565503,0.04408851,0.002648359,0.0006699031,0.0007427983,0.00003682109,0.00004075739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2150294,"threshold_uncertainty_score":0.6236395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1654921233235041,"score_gpt":0.4220172058259904,"score_spread":0.2565250825024863,"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."}}