{"id":"W4310876000","doi":"10.1039/d2ma00797e","title":"COVID-19 mitigation: nanotechnological intervention, perspective, and future scope","year":2022,"lang":"en","type":"article","venue":"Materials Advances","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"University of Calcutta; Department of Science and Technology, Ministry of Science and Technology, India","keywords":"Coronavirus disease 2019 (COVID-19); Globe; Scope (computer science); 2019-20 coronavirus outbreak; Perspective (graphical); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Pandemic; Intervention (counseling); Intensive care medicine; Medicine; Development economics; Political science; Environmental health; Virology; Economics; Psychiatry; Computer science; Pathology; Disease; Outbreak","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002275882,0.00009263977,0.0001777642,0.00008325696,0.0003061249,0.00003342791,0.00005564507,0.00004047182,0.001596138],"category_scores_gemma":[0.0003852118,0.00007995038,0.00003230694,0.0001782518,0.00008624413,0.00009208107,0.00009629145,0.000102983,0.00000833935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000142606,"about_ca_system_score_gemma":0.00003943057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003405031,"about_ca_topic_score_gemma":0.000006748206,"domain_scores_codex":[0.9992297,0.0000761073,0.000186114,0.000244133,0.0001477813,0.0001161309],"domain_scores_gemma":[0.999662,0.00003153648,0.00009468842,0.0001121125,0.00004712676,0.00005252318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000490334,0.0001458896,0.00102047,0.0002553265,0.00003454347,0.000115689,0.0004426119,0.000004809526,0.9754243,0.006484745,0.0004561176,0.01512518],"study_design_scores_gemma":[0.001265902,0.0005773558,0.0004972205,0.00002701506,0.0000247925,0.0006588029,0.005698731,0.000006213603,0.6157892,0.004725354,0.3705933,0.0001360941],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883551,0.004885201,0.000138803,0.004583034,0.0007670784,0.0002497396,0.00002357171,0.0002867388,0.0007107431],"genre_scores_gemma":[0.9954457,0.00009813104,0.001147818,0.002770883,0.0003265519,0.00009863928,0.000009855285,0.00001122834,0.00009116899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3701372,"threshold_uncertainty_score":0.9993165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02078964802392641,"score_gpt":0.3272999116329056,"score_spread":0.3065102636089791,"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."}}