{"id":"W2106833930","doi":"10.1586/14789450.2014.877346","title":"MRM for the verification of cancer biomarker proteins: recent applications to human plasma and serum","year":2014,"lang":"en","type":"review","venue":"Expert Review of Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia; University of Victoria","funders":"","keywords":"Biomarker; Biomarker discovery; Cancer; Selected reaction monitoring; Proteomics; Computational biology; Mass spectrometry; Medicine; Chemistry; Biology; Tandem mass spectrometry; Internal medicine; Chromatography","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":[0.0004639591,0.0004027269,0.001435173,0.00006126429,0.0001800934,0.00001646358,0.000723362,0.0002519652,0.00008852784],"category_scores_gemma":[0.0001205167,0.0002836167,0.0003509035,0.0003093724,0.0001316211,0.00003680831,0.0001626511,0.0002254338,0.000003082272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001360558,"about_ca_system_score_gemma":0.0001656137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003311098,"about_ca_topic_score_gemma":0.000007230189,"domain_scores_codex":[0.9977268,0.00003784056,0.001286763,0.0005503815,0.000177495,0.0002207413],"domain_scores_gemma":[0.9967076,0.0001519523,0.001453302,0.001296421,0.000305352,0.00008541047],"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":[0.000005381919,0.00004490659,3.321472e-7,0.1172234,0.00008109907,1.487854e-8,0.00001520523,2.163456e-7,0.003991415,0.002781129,0.0007106579,0.8751463],"study_design_scores_gemma":[0.00008927997,0.0000253834,1.520111e-7,0.04719117,0.0002717344,0.000002367302,0.00000463624,0.00001297132,0.01194345,0.0002210627,0.9399631,0.0002747138],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000001277316,0.8943263,0.09126981,0.0005489972,0.00001881173,0.01317789,0.0004697601,0.00004300628,0.0001442082],"genre_scores_gemma":[8.73491e-7,0.7777582,0.136262,0.00009586952,0.000142119,0.0854138,0.0001508975,0.00006940568,0.0001068162],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9392524,"threshold_uncertainty_score":0.9999616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05971793943924233,"score_gpt":0.425251734541624,"score_spread":0.3655337951023817,"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."}}