{"id":"W4200437116","doi":"10.1038/s41598-021-03309-5","title":"Identification of transcriptional regulatory network associated with response of host epithelial cells to SARS-CoV-2","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute; McGill University Health Centre; McGill University","funders":"Compute Canada; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Host (biology); Identification (biology); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Coronavirus disease 2019 (COVID-19); Host response; 2019-20 coronavirus outbreak; Biology; Computational biology; Host factors; Betacoronavirus; Virology; Immunology; Medicine; Genetics; Immune system; Infectious disease (medical specialty); Disease; Virus; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002036717,0.0002543811,0.0003569955,0.0004936727,0.0002231315,0.0003975914,0.0001841338,0.0001726293,0.001101721],"category_scores_gemma":[0.0004042302,0.0001104051,0.0005781645,0.0003962649,0.0001870574,0.0001910954,0.0002219943,0.0001909149,0.00008799317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004444246,"about_ca_system_score_gemma":0.0005564237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003356213,"about_ca_topic_score_gemma":0.00370586,"domain_scores_codex":[0.9999022,0.00002024693,0.000004492765,0.00003986145,0.00001538887,0.00001769469],"domain_scores_gemma":[0.9998934,0.00004767892,0.00002472812,0.000007161739,0.00001569285,0.00001128463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001184887,0.0003626681,0.1239457,0.0005815027,0.0004098129,0.0003804028,0.0002070767,0.5421932,0.2855341,0.005617645,0.001184645,0.03839844],"study_design_scores_gemma":[0.00002760991,0.0001409987,0.07019437,0.00001350055,0.0001022395,0.0001004468,0.000139303,0.9062601,0.01867457,0.003173584,0.001155372,0.00001785183],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9687653,0.000381574,0.02699299,0.0001315383,0.00001209604,0.0000399136,0.001970275,0.0002717738,0.001434601],"genre_scores_gemma":[0.987312,0.0002481895,0.009443304,0.00002999248,0.000005004003,0.00005473783,0.002476536,0.00001745387,0.0004127065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003356213,"threshold_uncertainty_score":0.006673396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03139035174516268,"score_gpt":0.3131975817401711,"score_spread":0.2818072299950085,"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."}}