{"id":"W4213151496","doi":"10.3389/fgene.2022.836798","title":"A Systematic Evaluation of Supervised Machine Learning Algorithms for Cell Phenotype Classification Using Single-Cell RNA Sequencing Data","year":2022,"lang":"en","type":"review","venue":"Frontiers in Genetics","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Western Canada Research Grid; Compute Canada","keywords":"Machine learning; Computer science; Artificial intelligence; Classifier (UML); Benchmark (surveying); Precision and recall; Algorithm; Support vector machine; F1 score; Data mining","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":[0.01334281,0.001889182,0.001633623,0.003511909,0.0009372592,0.001243592,0.00166053,0.001354316,0.000547513],"category_scores_gemma":[0.02523499,0.0004749496,0.001592308,0.002287514,0.0006002774,0.001791906,0.0008255607,0.001435726,0.0004362321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001026338,"about_ca_system_score_gemma":0.002013557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003469393,"about_ca_topic_score_gemma":0.002931136,"domain_scores_codex":[0.9901522,0.004344427,0.00110097,0.001466126,0.002727297,0.0002089932],"domain_scores_gemma":[0.9797467,0.01138056,0.0009286698,0.002093273,0.005633908,0.000216891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0008170409,0.001158175,0.02986404,0.001593467,0.001620909,0.0001614694,0.0001574575,0.2995032,0.01096908,0.002564645,0.007115947,0.6444745],"study_design_scores_gemma":[0.00006258739,0.0007359555,0.007203318,0.0001348911,0.0001361675,0.0001352637,0.00008096491,0.9759707,0.01174924,0.001236851,0.002511006,0.0000430426],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.4443364,0.01857119,0.5215972,0.0007069269,0.0006016864,0.001195012,0.002301211,0.005909974,0.004780445],"genre_scores_gemma":[0.5234231,0.003094058,0.4632377,0.000315145,0.000122686,0.0009780549,0.006936983,0.0003443487,0.001547941],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01334281,"threshold_uncertainty_score":0.07056439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2247234899502461,"score_gpt":0.3369404645989674,"score_spread":0.1122169746487214,"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."}}