{"id":"W2165384556","doi":"10.1074/mcp.r400004-mcp200","title":"HUPO Initiatives Relevant to Clinical Proteomics","year":2004,"lang":"en","type":"review","venue":"Molecular & Cellular Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Proteomics; Computational biology; Library science; Data science; Computer science; Biology; Genetics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.0007241178,0.001441484,0.002938985,0.000284535,0.0002930395,0.0001956189,0.001858635,0.001772264,0.000158356],"category_scores_gemma":[0.0004152558,0.00142992,0.001772111,0.0006838346,0.0002682073,0.0001467426,0.000940974,0.002684853,0.0005373089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008000481,"about_ca_system_score_gemma":0.001272096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000172294,"about_ca_topic_score_gemma":0.000001524127,"domain_scores_codex":[0.9935121,0.000204319,0.002587194,0.002064714,0.0005555202,0.001076165],"domain_scores_gemma":[0.9949461,0.0001295838,0.001383809,0.002667142,0.0002303982,0.000642945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001752073,0.002183331,0.00001191012,0.07804755,0.001822791,0.001397401,0.0002831977,0.000259059,0.1006585,0.04440195,0.0003322155,0.7704269],"study_design_scores_gemma":[0.0004184444,0.0001115903,7.258645e-8,0.01074295,0.0005746315,0.00006407622,0.00001070895,0.00001666944,0.2425935,0.00598216,0.7378634,0.001621878],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002958243,0.6783772,0.3117169,0.00009697471,0.0001286288,0.006078417,0.000356786,0.0005566467,0.00239261],"genre_scores_gemma":[0.00002130602,0.6229421,0.3703358,0.0001118409,0.0003535045,0.00489194,0.0005761673,0.0004012362,0.0003660021],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.768805,"threshold_uncertainty_score":0.9998335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04134999662326405,"score_gpt":0.370148911902081,"score_spread":0.328798915278817,"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."}}