{"id":"W2128789834","doi":"10.1373/clinchem.2009.127019","title":"The Bottleneck in the Cancer Biomarker Pipeline and Protein Quantification through Mass Spectrometry–Based Approaches: Current Strategies for Candidate Verification","year":2009,"lang":"en","type":"review","venue":"Clinical Chemistry","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":169,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Mount Sinai Hospital; University of Toronto","funders":"","keywords":"Biomarker discovery; Analyte; Selected reaction monitoring; Biomarker; Multiplex; Quantitative proteomics; Computer science; Chromatography; Mass spectrometry; Computational biology; Chemistry; Proteomics; Tandem mass spectrometry; Bioinformatics; Biology","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":[0.001073646,0.0004517283,0.0008019219,0.0000191151,0.0002605408,0.0002087847,0.0009376413,0.0005374089,0.00001806039],"category_scores_gemma":[0.0002682192,0.0002830273,0.0003663749,0.0003185903,0.0003233747,0.00007640753,0.00004431579,0.00099724,0.000002045407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001522696,"about_ca_system_score_gemma":0.0004704628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009001766,"about_ca_topic_score_gemma":0.000006124814,"domain_scores_codex":[0.9970521,0.00008110448,0.001383215,0.0009123518,0.0002080584,0.0003632226],"domain_scores_gemma":[0.9967949,0.0007975297,0.0009703261,0.001296196,0.0000767599,0.00006423745],"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":[0.00006446371,0.00032692,0.00001306543,0.01280611,0.00005208671,7.043624e-7,0.00001744555,0.000003406347,0.0008921262,0.003074815,0.001024863,0.981724],"study_design_scores_gemma":[0.0003306126,0.00001095534,0.000002151788,0.002605923,0.0002363424,0.000002532561,0.00009080364,0.0009559844,0.002410175,0.007126084,0.985807,0.0004214392],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001209811,0.9419975,0.0537134,0.0007930247,0.00003635961,0.002023394,0.0003719755,0.00009011507,0.000853191],"genre_scores_gemma":[0.0008529932,0.9820646,0.008038624,0.00002543472,0.0003934674,0.007311325,0.001034137,0.00005648485,0.0002229558],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9847822,"threshold_uncertainty_score":0.9999622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2137148214165347,"score_gpt":0.4544571271764846,"score_spread":0.2407423057599499,"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."}}