{"id":"W2039997444","doi":"10.1038/nmeth.3138","title":"Onco-proteogenomics: cancer proteomics joins forces with genomics","year":2014,"lang":"en","type":"article","venue":"Nature Methods","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":129,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; Ontario Institute for Cancer Research","funders":"Canadian Institutes of Health Research","keywords":"Proteogenomics; Proteomics; Computational biology; Proteome; Biology; Genomics; Genome; Cancer; Transcriptome; Bioinformatics; Gene; Genetics; Gene expression","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005083943,0.0003134727,0.0003592021,0.00005946117,0.0002289104,0.0000581565,0.000507941,0.0005842449,0.0001722482],"category_scores_gemma":[0.0001030515,0.0002595747,0.0001049394,0.000185699,0.0001134939,0.00009716643,0.0001154565,0.001206629,0.000006205892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002491392,"about_ca_system_score_gemma":0.0001217766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004148854,"about_ca_topic_score_gemma":0.00003313198,"domain_scores_codex":[0.9985299,0.00005863783,0.0003030558,0.0005608813,0.0001563087,0.0003911945],"domain_scores_gemma":[0.9985024,0.0001464694,0.0002823833,0.0007963718,0.0001363483,0.0001359985],"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":[0.00009928348,0.00004313702,0.0004236753,0.0001079928,0.00005717513,9.727775e-7,0.0001120182,0.0003517125,0.888983,0.01643947,0.0001680411,0.09321348],"study_design_scores_gemma":[0.0003208599,0.00003129953,0.00002253586,0.00003966388,0.00003723483,0.00001170753,0.00002443279,0.001708225,0.7426098,0.0157259,0.2391401,0.0003283005],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07671656,0.0005979958,0.9028881,0.0005843799,0.00007028707,0.0006373809,0.00006823365,0.0003535075,0.01808353],"genre_scores_gemma":[0.02719394,0.0002156724,0.9691252,0.0005073476,0.0005199735,0.001110316,0.00002921593,0.00009861881,0.001199706],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.238972,"threshold_uncertainty_score":0.9999856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01374175549070463,"score_gpt":0.3649553605235688,"score_spread":0.3512136050328641,"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."}}