{"id":"W3122900665","doi":"10.1109/bibm49941.2020.9313378","title":"Unsupervised Identification of SARS-CoV-2 Target Cell Groups via Nonlinear Dimensionality Reduction on Single-cell RNA-Seq Data","year":2020,"lang":"en","type":"article","venue":"","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cluster analysis; Dimensionality reduction; Computer science; Normalization (sociology); Artificial intelligence; Identification (biology); Data mining; Machine learning; Computational biology; Pattern recognition (psychology); Biology","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":[0.0008287529,0.0005986486,0.0007796847,0.001427134,0.0004621025,0.0007630243,0.0004711434,0.0004808263,0.0004947148],"category_scores_gemma":[0.001656274,0.000192748,0.001070004,0.001036907,0.0004313868,0.0004074739,0.000618104,0.0006602253,0.0005084104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004665513,"about_ca_system_score_gemma":0.0008099211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003323868,"about_ca_topic_score_gemma":0.004863373,"domain_scores_codex":[0.9993123,0.0001508171,0.00005120978,0.0002368533,0.0001603249,0.00008849481],"domain_scores_gemma":[0.999268,0.0002453336,0.0000830676,0.0001062629,0.0002551462,0.00004226448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001328737,0.0005489448,0.0519041,0.0007914359,0.0005050904,0.0005760348,0.001334115,0.09797206,0.6307664,0.002087925,0.005488718,0.2066964],"study_design_scores_gemma":[0.00003801073,0.000200297,0.06000492,0.00003068563,0.0001139653,0.0002697498,0.0005323141,0.8158431,0.114855,0.003725617,0.004265254,0.0001212568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7020236,0.0006971695,0.2905701,0.0002977757,0.00007388108,0.0002505163,0.003623857,0.001520222,0.0009428114],"genre_scores_gemma":[0.700638,0.0005845014,0.2832256,0.0001623788,0.00004902322,0.0005078444,0.01301925,0.0002452218,0.001568096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003323868,"threshold_uncertainty_score":0.006609082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06605427453292381,"score_gpt":0.2682792193442576,"score_spread":0.2022249448113338,"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."}}