{"id":"W2077333201","doi":"10.1074/mcp.m600378-mcp200","title":"Endometrial Carcinoma Biomarker Discovery and Verification Using Differentially Tagged Clinical Samples with Multidimensional Liquid Chromatography and Tandem Mass Spectrometry","year":2007,"lang":"en","type":"article","venue":"Molecular & Cellular Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; Mount Sinai Hospital; University of Toronto; York University","funders":"","keywords":"Biomarker discovery; Chromatography; Tandem mass spectrometry; Mass spectrometry; Liquid chromatography–mass spectrometry; Biomarker; Chemistry; Proteomics","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":[0.0005229001,0.0003456065,0.0004022444,0.0002189906,0.0002352418,0.0001003683,0.0001647149,0.0002903969,0.00001578162],"category_scores_gemma":[0.00007541482,0.0003250068,0.0001413955,0.0003605259,0.0003459425,0.0001483097,0.0001387494,0.0003693116,6.167749e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007217399,"about_ca_system_score_gemma":0.00006821949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003728892,"about_ca_topic_score_gemma":0.000003274435,"domain_scores_codex":[0.9978865,0.0000527544,0.0006049129,0.0007446061,0.0003027893,0.0004084719],"domain_scores_gemma":[0.9987348,0.000123137,0.0003443215,0.0005156891,0.00008422432,0.0001978054],"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":[0.0005702868,0.0001096792,0.01417022,0.00005141879,0.00009214994,0.0000384849,0.00001530499,0.000005424974,0.983275,0.001400451,9.634248e-7,0.0002706003],"study_design_scores_gemma":[0.00172726,0.0001481435,0.002814104,0.00005095906,0.0001112455,0.00004949833,0.00003712922,0.0009005149,0.9929896,0.0006591707,0.0001001988,0.0004121615],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5297669,0.0002953842,0.4693852,0.00001690508,0.00001854355,0.0004024564,0.00002517204,0.00005331783,0.0000361624],"genre_scores_gemma":[0.6507943,0.00007709141,0.3488518,0.00002072467,0.00007201803,0.00003978904,0.00008529062,0.00005014369,0.000008907627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1210274,"threshold_uncertainty_score":0.9999202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02267820828143937,"score_gpt":0.2788860935640393,"score_spread":0.2562078852826,"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."}}