{"id":"W2148319526","doi":"10.1021/pr7005999","title":"“Product Ion Monitoring” Assay for Prostate-Specific Antigen in Serum Using a Linear Ion-Trap","year":2008,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network; Mount Sinai Hospital","funders":"","keywords":"Detection limit; Chemistry; Ion trap; Biomarker discovery; Mass spectrometry; Chromatography; Prostate-specific antigen; Peptide; Biomarker; Proteomics; Prostate cancer; Biochemistry; Biology; Cancer","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001740718,0.001155136,0.0005199634,0.0006498893,0.000359331,0.0007927906,0.001050998,0.001074427,0.0007773975],"category_scores_gemma":[0.002677365,0.0003351711,0.0005495499,0.0004827938,0.0005800129,0.0008019686,0.0006806608,0.0009638118,0.000932545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003376364,"about_ca_system_score_gemma":0.0006598139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00027393,"about_ca_topic_score_gemma":0.0003725132,"domain_scores_codex":[0.9980205,0.0005892972,0.00008824886,0.0005275637,0.0006868448,0.00008747847],"domain_scores_gemma":[0.9992828,0.0002545501,0.0001855432,0.00006921789,0.0001512749,0.00005663668],"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":[0.0001552634,0.00006019467,0.001554914,0.0001743647,0.00005163361,0.00007721192,0.00003205882,0.0002550489,0.9821823,0.000247208,0.0003645096,0.01484525],"study_design_scores_gemma":[0.00002512787,0.0006825211,0.004462415,0.00001853877,0.00007992506,0.001241222,0.00002729738,0.009225614,0.9800118,0.0002567228,0.003930946,0.00003797554],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3008446,0.004486368,0.6828458,0.0007590301,0.0002757498,0.0006393034,0.001386737,0.004020495,0.004741903],"genre_scores_gemma":[0.5263581,0.002690162,0.46376,0.001158054,0.0001551785,0.0007239166,0.001985741,0.0001462506,0.003022561],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001740718,"threshold_uncertainty_score":0.009205937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1588476237780264,"score_gpt":0.4130124774335155,"score_spread":0.2541648536554891,"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."}}