{"id":"W1979340580","doi":"10.1038/nmeth.2650","title":"TCPA: a resource for cancer functional proteomics data","year":2013,"lang":"en","type":"letter","venue":"Nature Methods","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":538,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Cancer Institute; Canada's Michael Smith Genome Sciences Centre; University of Miami; Susan G. Komen for the Cure","keywords":"Proteomics; Computational biology; Resource (disambiguation); Biology; Computer science; Bioinformatics; Genetics; Gene","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":[0.007980788,0.0009364429,0.001303185,0.001365228,0.002166396,0.004488468,0.002992734,0.01396611,0.01164807],"category_scores_gemma":[0.03179784,0.00120382,0.001060853,0.001273451,0.002246103,0.006997826,0.004741713,0.02066441,0.01764726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003126903,"about_ca_system_score_gemma":0.002622527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001743611,"about_ca_topic_score_gemma":0.003259629,"domain_scores_codex":[0.9957666,0.0008027627,0.0003937304,0.0002976537,0.002361877,0.0003773915],"domain_scores_gemma":[0.9831782,0.008038908,0.0007280501,0.002019056,0.00379956,0.002236286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006929669,0.00001039746,0.00006518065,0.00005348647,0.00001024001,0.0002077382,0.00001640741,0.00006794263,0.0008945701,0.002703401,0.9818475,0.01405396],"study_design_scores_gemma":[0.0001056247,0.00002962005,0.0001999492,0.00008271204,0.00001864377,0.0006336939,0.00003470645,0.001849309,0.002183478,0.02078083,0.9740351,0.00004626672],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"software","genre_scores_codex":[0.0009958614,0.00528659,0.03164446,0.8587254,0.08568112,0.0001502325,0.003386358,0.004118667,0.01001127],"genre_scores_gemma":[0.01561018,0.007839378,0.04620834,0.7644966,0.09814368,0.0009975227,0.005204258,0.002221463,0.05927857],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01396611,"threshold_uncertainty_score":0.042207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07253778142216777,"score_gpt":0.4263131586805006,"score_spread":0.3537753772583328,"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."}}