{"id":"W4321077501","doi":"10.1038/s41587-023-01657-3","title":"TACCO unifies annotation transfer and decomposition of cell identities for single-cell and spatial omics","year":2023,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; Office of Extramural Research, National Institutes of Health; National Cancer Institute; National Human Genome Research Institute; Council for Higher Education; Hebrew University of Jerusalem; Ludwig Center at Harvard; Deutsche Forschungsgemeinschaft; National Institutes of Health; U.S. Department of Health and Human Services; National Institute of Mental Health; Human Frontier Science Program; European Commission; Klarman Cell Observatory, Broad Institute; Google; Azrieli Foundation; Israel Science Foundation; National Institute of Allergy and Infectious Diseases; Howard Hughes Medical Institute","keywords":"Annotation; DECIPHER; Computer science; Dropout (neural networks); Matching (statistics); Variety (cybernetics); Transfer (computing); Data mining; Computational biology; Biological system; Artificial intelligence; Machine learning; Biology; Bioinformatics; Mathematics","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":[0.003130008,0.001833802,0.001548889,0.001584576,0.001248348,0.003142572,0.002759936,0.002883531,0.00334912],"category_scores_gemma":[0.009961053,0.0009267287,0.00277943,0.00172738,0.001584532,0.002808454,0.005071885,0.00315124,0.002438602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001490613,"about_ca_system_score_gemma":0.003597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007218397,"about_ca_topic_score_gemma":0.007978935,"domain_scores_codex":[0.9989125,0.0002611106,0.0000731093,0.0003837297,0.0002595987,0.0001099856],"domain_scores_gemma":[0.995945,0.001213325,0.0002232651,0.001686908,0.0006577914,0.0002737061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000496474,0.0003534526,0.004335133,0.0005425678,0.000330835,0.0003629252,0.0004668868,0.7027606,0.03841444,0.06435034,0.01742947,0.1701568],"study_design_scores_gemma":[0.000009452578,0.00002510841,0.0003062257,0.00001345441,0.00001171394,0.00005225043,0.00002559611,0.9739908,0.004776363,0.01658375,0.004181151,0.00002408153],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007392578,0.0000813623,0.9845386,0.0001652538,0.0001066218,0.00007065994,0.0005126478,0.006195157,0.0009372199],"genre_scores_gemma":[0.1330056,0.0002255197,0.8548604,0.0003575698,0.0001585955,0.000631496,0.004285193,0.003472124,0.003003531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007218397,"threshold_uncertainty_score":0.01655322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0076335608333301,"score_gpt":0.2322385190547115,"score_spread":0.2246049582213814,"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."}}