{"id":"W2128564638","doi":"10.1021/pr300014s","title":"Interlaboratory Reproducibility of Selective Reaction Monitoring Assays Using Multiple Upfront Analyte Enrichment Strategies","year":2012,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Mount Sinai Hospital","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Cancer Institute","keywords":"Analyte; Reproducibility; Multiplex; Mass spectrometry; Chromatography; Selected reaction monitoring; Immunoassay; Sample preparation; Chemistry; Tandem mass spectrometry; Medicine; Bioinformatics; Biology; Antibody","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":[],"consensus_categories":[],"category_scores_codex":[0.006625293,0.0001111175,0.0002755837,0.0003405285,0.0001291986,0.00004550292,0.0002708013,0.0001071638,0.0001568548],"category_scores_gemma":[0.000939523,0.00009598635,0.0001081513,0.000725007,0.00009010963,0.0005167339,0.0001037914,0.0009715554,0.000001629632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009115566,"about_ca_system_score_gemma":0.0003068011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001831365,"about_ca_topic_score_gemma":0.000002468483,"domain_scores_codex":[0.9977539,0.0001653636,0.000611457,0.0002885965,0.0008003231,0.0003803394],"domain_scores_gemma":[0.9971079,0.0001504702,0.0005157885,0.000689681,0.001389067,0.000147156],"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":[0.00009456818,0.0003496043,0.05319081,0.0001377948,0.00006968187,0.000001759222,0.0002856324,0.00001363537,0.9446265,0.0001824711,0.00006050378,0.0009870622],"study_design_scores_gemma":[0.0001815468,0.0001268407,0.009872815,0.000130512,0.00001971573,0.0000232423,0.001975662,0.0001752826,0.9859623,0.001003749,0.0004414889,0.00008684294],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938691,0.0004899371,0.001938566,0.00006966983,0.00005262419,0.0002334227,0.000006415675,0.00002015948,0.00332012],"genre_scores_gemma":[0.9869031,0.0000792152,0.01228273,4.56974e-7,0.0006021037,0.00003308549,8.861082e-7,0.000015676,0.00008275903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.043318,"threshold_uncertainty_score":0.4220979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1131721614706311,"score_gpt":0.4223994220565561,"score_spread":0.309227260585925,"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."}}