{"id":"W3131971476","doi":"10.37044/osf.io/b4zkp","title":"Global analysis of human SARS-CoV-2 infection and host-virus interaction","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Health","funders":"China Scholarship Council","keywords":"Workflow; Context (archaeology); Host (biology); Computational biology; Transcriptome; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Human interaction; Computer science; Gene; Biology; Virology; Gene expression; Medicine; Genetics; Human–computer interaction; Database","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009662032,0.0004092519,0.0007234376,0.000980358,0.0002131049,0.000707316,0.0002323255,0.0002581385,0.00187842],"category_scores_gemma":[0.000870212,0.0001496464,0.000753183,0.001390629,0.0002418401,0.0003172026,0.0006078893,0.0004172589,0.0004208772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003598052,"about_ca_system_score_gemma":0.0004354435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001183949,"about_ca_topic_score_gemma":0.001293237,"domain_scores_codex":[0.9994934,0.0001070228,0.00002181989,0.0001976382,0.0001043748,0.00007583827],"domain_scores_gemma":[0.9995337,0.0001994939,0.00005549332,0.00007419944,0.00008148888,0.00005559836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002770812,0.0003364192,0.1037845,0.0009870799,0.0005816256,0.0003007637,0.0003914701,0.03226824,0.7493331,0.002001771,0.008776336,0.0984678],"study_design_scores_gemma":[0.0000743013,0.001249079,0.6073129,0.00006959801,0.0004001861,0.0006679794,0.0006126427,0.1019126,0.2608604,0.005361029,0.02133364,0.0001457441],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9159354,0.001456544,0.05267386,0.0002430583,0.00008606516,0.00009217431,0.02479676,0.002135472,0.002580681],"genre_scores_gemma":[0.8879546,0.0008812758,0.05240358,0.0002260883,0.00004585883,0.0002759887,0.05526071,0.000481649,0.002470303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00187842,"threshold_uncertainty_score":0.006283939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02917195274783961,"score_gpt":0.3048110112594162,"score_spread":0.2756390585115766,"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."}}