{"id":"W2137575882","doi":"10.1155/2004/579363","title":"Advancement of Biomarker Discovery and Validation through the HUPO Plasma Proteome Project","year":2004,"lang":"en","type":"article","venue":"Disease Markers","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Diabetes and Digestive and Kidney Diseases; National Institute on Aging; Abbott Fund; Bristol-Myers Squibb Canada; National Institute of Environmental Health Sciences; University of Michigan; National Institutes of Health; Michigan Economic Development Corporation; Procter and Gamble; National Cancer Institute; National Institute on Alcohol Abuse and Alcoholism; Johnson Family Foundation; Bristol-Myers Squibb; Novartis; Pfizer","keywords":"Biomarker; Proteome; Biomarker discovery; Computational biology; Data science; Library science; Proteomics; Political science; Bioinformatics; Biology; Computer science; Genetics","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":[0.0291568,0.0007269633,0.0009047592,0.001702555,0.0008486923,0.002297825,0.001216009,0.0009111514,0.001227993],"category_scores_gemma":[0.01195438,0.0002972276,0.0005018431,0.00130838,0.0008784336,0.001453075,0.002973148,0.001696305,0.0007178591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007703361,"about_ca_system_score_gemma":0.006430771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001759097,"about_ca_topic_score_gemma":0.001000598,"domain_scores_codex":[0.9932466,0.003768791,0.0002768821,0.0005670036,0.001739039,0.0004017392],"domain_scores_gemma":[0.9910309,0.00239947,0.0006800496,0.001097915,0.00371452,0.001077062],"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":[0.004569042,0.002179211,0.05796924,0.0009874394,0.0004441241,0.0006500301,0.0008592384,0.003055118,0.1982929,0.02872698,0.02533365,0.6769331],"study_design_scores_gemma":[0.001268012,0.005247108,0.09432444,0.0006213921,0.0004591317,0.002072774,0.0006692417,0.01789581,0.5376599,0.01732699,0.3223121,0.0001431117],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.488111,0.03100251,0.4122197,0.02440979,0.001370357,0.003283554,0.01108948,0.00198751,0.02652602],"genre_scores_gemma":[0.451621,0.0128855,0.5053443,0.003650171,0.0006330549,0.001833745,0.01733745,0.0002861502,0.006408646],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0291568,"threshold_uncertainty_score":0.1541977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01792852214372989,"score_gpt":0.2909472552616769,"score_spread":0.273018733117947,"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."}}