{"id":"W4379520413","doi":"10.1101/2023.06.05.543335","title":"Illuminating Dark Proteins using Reactome Pathways","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research","funders":"Common Fund; National Institute on Drug Abuse; National Human Genome Research Institute; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; NIH Office of the Director; National Heart, Lung, and Blood Institute; National Cancer Institute; National Institutes of Health","keywords":"Computer science; Computational biology; Visualization; Random forest; Fuzzy logic; Biological pathway; Gene; Bioinformatics; Artificial intelligence; Biology; Gene expression; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006321345,0.0006761508,0.0005447405,0.0002084062,0.0002517448,0.0002028932,0.0007071082,0.0009875733,0.000008621765],"category_scores_gemma":[0.0003481721,0.0007670267,0.0002886747,0.0003362449,0.0001644226,0.00001159039,0.0006882706,0.0007337577,0.00003619685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001486843,"about_ca_system_score_gemma":0.0007127597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001671786,"about_ca_topic_score_gemma":0.00001041546,"domain_scores_codex":[0.9967447,0.0001429984,0.0006214555,0.001364409,0.0003835056,0.0007429333],"domain_scores_gemma":[0.9974184,0.00002261721,0.0004219819,0.001453667,0.0004166406,0.0002667032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003399126,0.0001114263,0.003614493,0.0003354067,0.0001459676,0.000050806,0.00001125092,0.0001351274,0.9953743,0.00005111928,0.0001333807,0.000002791552],"study_design_scores_gemma":[0.0005206952,0.0001196937,0.009259114,0.0004523629,0.0001049251,5.427709e-8,0.000006754483,0.0008913614,0.9852089,0.000003868861,0.002325079,0.001107217],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99024,0.0006018973,0.005878652,0.00005638678,0.001685604,0.0008347661,0.0003648085,0.0003175154,0.0000203602],"genre_scores_gemma":[0.9875413,0.0002133138,0.01040909,0.00013188,0.001227476,0.0001413577,0.000004892533,0.0003130202,0.00001771149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01016537,"threshold_uncertainty_score":0.999478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03452337078943758,"score_gpt":0.2315212256543912,"score_spread":0.1969978548649536,"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."}}