{"id":"W2952568226","doi":"10.1101/562082","title":"Evaluation of methods to assign cell type labels to cell clusters from single-cell RNAsequencing data","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; Princess Margaret Cancer Centre; Ontario Institute for Cancer Research; University of Toronto; University Health Network","funders":"","keywords":"Cell type; Computer science; Cell; Cluster analysis; Normalization (sociology); Hierarchical clustering; Computational biology; Data mining; Artificial intelligence; Biology; Genetics","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":[0.0236815,0.003792702,0.002682062,0.006776263,0.001843896,0.004291938,0.004657426,0.003618323,0.002209064],"category_scores_gemma":[0.0321895,0.0008745473,0.003901488,0.003086311,0.001290601,0.00226645,0.002471654,0.002379765,0.001508309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003335461,"about_ca_system_score_gemma":0.004150311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01954254,"about_ca_topic_score_gemma":0.01474713,"domain_scores_codex":[0.9903733,0.003581,0.0007961587,0.002384363,0.002131017,0.0007341402],"domain_scores_gemma":[0.9770518,0.0152328,0.0008435094,0.002192515,0.004126208,0.0005532545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002584922,0.00100365,0.05289335,0.00220976,0.005197272,0.0003294793,0.0005252602,0.3579331,0.03366818,0.003775387,0.02416742,0.5157123],"study_design_scores_gemma":[0.0001276639,0.0002955035,0.007042563,0.0001125243,0.0002464649,0.0001681838,0.0001913001,0.961481,0.02353958,0.002849075,0.003851954,0.00009422943],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3970834,0.01194243,0.5077548,0.001898198,0.001993021,0.001310718,0.009191936,0.06271459,0.006110782],"genre_scores_gemma":[0.4259405,0.001147546,0.5395025,0.001209674,0.0002691453,0.0009249276,0.02395027,0.003906222,0.003149183],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0236815,"threshold_uncertainty_score":0.1252413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07608679451152739,"score_gpt":0.3034211514138141,"score_spread":0.2273343569022867,"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."}}