{"id":"W2168447402","doi":"10.1016/s1535-9476(20)31954-x","title":"What Has Proteomics Accomplished?","year":2007,"lang":"en","type":"article","venue":"Molecular & Cellular Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Proteomics; Computational biology; Computer science; Chemistry; Biology; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.06551424,0.002218914,0.002812185,0.004519443,0.006364924,0.02734177,0.002681304,0.01249065,0.0101978],"category_scores_gemma":[0.04992617,0.001101807,0.001753457,0.004374401,0.02777924,0.03927802,0.00911977,0.02263115,0.008701832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01063977,"about_ca_system_score_gemma":0.01839039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004505447,"about_ca_topic_score_gemma":0.002616445,"domain_scores_codex":[0.9662013,0.01430038,0.002274567,0.005920419,0.009071541,0.002231692],"domain_scores_gemma":[0.9529189,0.02287724,0.002048349,0.004404615,0.01072996,0.007020876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001885531,0.00009773593,0.001456151,0.005032186,0.0002152993,0.0002770352,0.002592399,0.0003166445,0.0009284237,0.3034209,0.4474785,0.2379962],"study_design_scores_gemma":[0.00001474422,0.00007619872,0.0008023538,0.002805173,0.00002449772,0.00029981,0.001919941,0.0001106493,0.0003114151,0.1316519,0.8619195,0.00006379569],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0006309784,0.3876146,0.006107254,0.5498813,0.03958473,0.00004285028,0.0001865289,0.0002350457,0.01571663],"genre_scores_gemma":[0.03386374,0.483363,0.0161043,0.3950462,0.05545436,0.0002892796,0.000591115,0.0003717567,0.01491623],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.06551424,"threshold_uncertainty_score":0.3464766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01567782660482321,"score_gpt":0.2592962059590678,"score_spread":0.2436183793542446,"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."}}