{"id":"W2619565830","doi":"10.1002/jms.3932","title":"Current trends in quantitative proteomics – an update","year":2017,"lang":"en","type":"review","venue":"Journal of Mass Spectrometry","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital; Genome British Columbia; University of Victoria","funders":"Fondation De Famille Alvin Segal; Genome British Columbia; Genome Canada; Segal Family Foundation; Leading Edge Endowment Fund; McGill University","keywords":"Chemistry; Current (fluid); Proteomics; Chromatography; Computational biology; Biochemistry; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005194366,0.0004280978,0.001828665,0.001039024,0.00009432882,0.0001103598,0.001241911,0.0003196669,0.0003457705],"category_scores_gemma":[0.00009471449,0.0003544975,0.0006572754,0.0004206455,0.00007287043,0.0003184351,0.00009288352,0.00206134,0.00001261423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005465489,"about_ca_system_score_gemma":0.0002279586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002251488,"about_ca_topic_score_gemma":0.000003817318,"domain_scores_codex":[0.9976695,0.00005301234,0.001286551,0.0003440755,0.0003093088,0.0003375468],"domain_scores_gemma":[0.9955463,0.00006203879,0.003328504,0.000785272,0.0001140273,0.0001638849],"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":[0.00002277743,0.0002328161,0.00001282394,0.002435442,0.00009728765,0.00005247576,0.0000172533,0.000001530215,0.0003254816,0.003083337,0.0001657289,0.993553],"study_design_scores_gemma":[0.0002810258,0.0001239859,0.000003146531,0.006770421,0.0002612588,0.0001778124,0.0000159281,0.00001079822,0.0005017701,0.007946561,0.9834642,0.0004431071],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006922166,0.9884263,0.009291229,0.00004150268,0.000109134,0.0001831911,0.0001137069,0.00002768971,0.001738078],"genre_scores_gemma":[0.00001856304,0.8367923,0.1624956,0.000002490051,0.0003707726,0.000057431,0.00005651716,0.00006495675,0.0001413781],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9931099,"threshold_uncertainty_score":0.9998907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09637483988085828,"score_gpt":0.4414650614813009,"score_spread":0.3450902216004427,"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."}}