{"id":"W1993864534","doi":"10.1016/j.ab.2006.03.037","title":"Mass spectrometric quantitation of C-reactive protein using labeled tryptic peptides","year":2006,"lang":"en","type":"article","venue":"Analytical Biochemistry","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Chromatography; Chemistry; Mass spectrometry","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":[0.001167336,0.001349435,0.0006777279,0.001300419,0.001052257,0.0008089916,0.001285738,0.00134391,0.001524397],"category_scores_gemma":[0.001248463,0.000563624,0.0004624338,0.001295159,0.0005290658,0.0008219755,0.0003716776,0.001800343,0.001181501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008364617,"about_ca_system_score_gemma":0.0007083842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007474747,"about_ca_topic_score_gemma":0.001650837,"domain_scores_codex":[0.9990174,0.0001468798,0.00006671219,0.000286789,0.0003831495,0.00009912578],"domain_scores_gemma":[0.9985788,0.0003438932,0.0001716215,0.0001535023,0.0005322774,0.0002199058],"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":[0.0001287859,0.00007509013,0.000157678,0.00004548873,0.00001098574,0.00003527629,0.00001746252,0.00003742343,0.9973723,0.0001344842,0.0001133821,0.00187167],"study_design_scores_gemma":[0.00002267402,0.0001809612,0.002186921,0.00001142608,0.00002176463,0.0003696187,0.00001585147,0.002004943,0.9939773,0.0001417054,0.00105552,0.00001134145],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6847049,0.006184147,0.2966213,0.0007264942,0.0007098904,0.0006396908,0.002170011,0.001704856,0.006538791],"genre_scores_gemma":[0.5985819,0.006110279,0.3743669,0.0015715,0.0002640307,0.001052371,0.005873659,0.0003254981,0.0118539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001524397,"threshold_uncertainty_score":0.006173551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01492487467017963,"score_gpt":0.2865720853827217,"score_spread":0.2716472107125421,"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."}}