{"id":"W3124723126","doi":"10.20944/preprints202008.0253.v1","title":"Prediction and Analysis of SARS-CoV-2-Targeting &lt;i&gt;microRNA&lt;/i&gt; in Human Lung Epithelium","year":2020,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto","funders":"","keywords":"microRNA; Coronavirus; Biology; Virology; RNA; Mechanism (biology); Coronavirus disease 2019 (COVID-19); Immunology; Gene; Genetics; Disease; Medicine; Pathology; Infectious disease (medical specialty)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006919312,0.0004225205,0.0006841802,0.000407691,0.00007860803,0.00002295891,0.0004589234,0.0006000017,0.00005939522],"category_scores_gemma":[0.0002771411,0.0005020492,0.0003991261,0.000386893,0.0001563217,0.00000993183,0.001783237,0.0003647426,0.00001151561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001010461,"about_ca_system_score_gemma":0.0001290578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004999308,"about_ca_topic_score_gemma":0.00008056881,"domain_scores_codex":[0.9967924,0.0002621148,0.0009419572,0.001386439,0.0002782417,0.0003388363],"domain_scores_gemma":[0.9979529,0.00001925474,0.000666003,0.001054784,0.0001984882,0.000108563],"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":[0.00006738848,0.00008335221,0.2519292,0.0002616431,0.0009261508,0.000003823845,0.0001950875,0.001330922,0.7449834,0.00004430834,0.0001261912,0.00004853266],"study_design_scores_gemma":[0.0003023299,0.0000166147,0.4116634,0.00008241223,0.0006143315,0.000001282272,0.000008156095,0.002161655,0.5839707,0.0001536607,0.0007600571,0.0002654516],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957144,0.001454714,0.0009204424,0.000111656,0.0001551473,0.0006342204,0.0002908304,0.00004661289,0.0006720045],"genre_scores_gemma":[0.9968349,0.000384792,0.0003118296,0.0000568699,0.0001991156,0.00007975454,0.002006114,0.0000580514,0.00006855186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1610128,"threshold_uncertainty_score":0.9997431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05082982092555497,"score_gpt":0.3166939297280539,"score_spread":0.2658641088024989,"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."}}