{"id":"W2953151710","doi":"10.1016/j.cels.2019.03.003","title":"DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors","year":2019,"lang":"en","type":"article","venue":"Cell Systems","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4592,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Institute of General Medical Sciences; University of California, San Francisco; Common Fund; York University; Damon Runyon Cancer Research Foundation; Eunice Kennedy Shriver National Institute of Child Health and Human Development; California Institute of Technology; U.S. Department of Defense; National Institutes of Health; National Science Foundation","keywords":"Spurious relationship; Computational biology; Gene; Gene expression; Identification (biology); Biology; RNA; Expression (computer science); Limit (mathematics); Cell; RNA-Seq; Biological system; Computer science; Pattern recognition (psychology); Genetics; Artificial intelligence; Transcriptome; Mathematics; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003053569,0.001155432,0.001235734,0.002148689,0.00104964,0.001509401,0.002123129,0.001780503,0.006981205],"category_scores_gemma":[0.006713698,0.001060314,0.0008651081,0.001679619,0.0004592654,0.001555707,0.001571123,0.001502165,0.003521521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007677261,"about_ca_system_score_gemma":0.001106225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002257481,"about_ca_topic_score_gemma":0.005963511,"domain_scores_codex":[0.9987747,0.0002305481,0.00009055244,0.0004025945,0.000418695,0.00008282832],"domain_scores_gemma":[0.9978899,0.001157493,0.0002315062,0.0003757182,0.0002143342,0.0001309761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002381545,0.0005561515,0.01055165,0.001448131,0.0006460081,0.0005833209,0.0006564923,0.04182786,0.2164012,0.01458933,0.07202133,0.6383371],"study_design_scores_gemma":[0.0001252859,0.000157843,0.003059315,0.00004903842,0.00005978933,0.0003274389,0.00008950438,0.8583856,0.1049316,0.01303557,0.019646,0.0001330323],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03558873,0.0003219217,0.8859389,0.0001502352,0.000226461,0.0002062629,0.00812761,0.06826566,0.00117433],"genre_scores_gemma":[0.08946794,0.000124339,0.8988015,0.0001101874,0.00004230549,0.0005496317,0.005511365,0.002970527,0.002422229],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006981205,"threshold_uncertainty_score":0.02335441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06194647511084914,"score_gpt":0.2449073005294619,"score_spread":0.1829608254186127,"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."}}