{"id":"W4413140408","doi":"10.1109/tcbbio.2025.3548094","title":"DIC: Deep Imputing and Clustering Single Cell RNA Sequencing Data","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Computational Biology and Bioinformatics","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cluster analysis; Deep sequencing; Computer science; Computational biology; RNA; Artificial intelligence; Data mining; Biology; Genetics; Gene","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":[0.001783944,0.0009688174,0.0008157837,0.0006027963,0.0004858644,0.000700826,0.00228517,0.001206072,0.001362102],"category_scores_gemma":[0.00280906,0.0005095034,0.0008695874,0.0006888601,0.0007373038,0.001040296,0.002037877,0.002232695,0.0007275968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009280886,"about_ca_system_score_gemma":0.001490483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004527187,"about_ca_topic_score_gemma":0.00584307,"domain_scores_codex":[0.9994247,0.00009787414,0.00002856692,0.0002108777,0.000163658,0.00007424656],"domain_scores_gemma":[0.99913,0.000240837,0.00009211273,0.0002549487,0.0002010885,0.0000811788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005049233,0.0002466304,0.007711318,0.0003284145,0.000357334,0.0003719851,0.0002116926,0.5254803,0.06064759,0.01577758,0.0183074,0.3700549],"study_design_scores_gemma":[0.0000126277,0.00004004843,0.0005763777,0.000006936097,0.00001336419,0.00006358153,0.00001119104,0.9799529,0.01342945,0.003728644,0.002148482,0.0000162939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01596454,0.0002657024,0.9787408,0.000195153,0.00007345586,0.00006411775,0.000517875,0.003378607,0.0007996834],"genre_scores_gemma":[0.2579806,0.000505552,0.7284502,0.0008979178,0.0001059747,0.0003700641,0.004904204,0.0004709171,0.006314673],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004527187,"threshold_uncertainty_score":0.009434462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02355678786869936,"score_gpt":0.2627424157193676,"score_spread":0.2391856278506683,"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."}}