{"id":"W4206353179","doi":"10.1002/9780470117118.ch13b","title":"Enhanced Proteomic Analysis by HPLC Prefractionation","year":2006,"lang":"en","type":"other","venue":"","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Chromatography; Chemistry; Computer science; Computational biology; Biology","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":[0.0005230563,0.002068058,0.001257816,0.001413235,0.0005546443,0.0008806071,0.001244701,0.0006944375,0.02626281],"category_scores_gemma":[0.0005597189,0.0007301408,0.0009595343,0.001256532,0.0002360633,0.001238434,0.0006221134,0.001968253,0.03131925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004482175,"about_ca_system_score_gemma":0.0006942241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005327521,"about_ca_topic_score_gemma":0.001732026,"domain_scores_codex":[0.999341,0.00005656947,0.00003432139,0.0001500032,0.0003477838,0.00007036426],"domain_scores_gemma":[0.9997489,0.00005530496,0.0000241184,0.00004287647,0.0001101001,0.00001877323],"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":[0.00009596795,0.0001658682,0.00009516828,0.0008237527,0.00003671297,0.0001662939,0.00002620067,0.0001459175,0.920222,0.00124647,0.01409983,0.06287576],"study_design_scores_gemma":[0.00002809326,0.0001688322,0.001852308,0.00008810181,0.00005890748,0.0007333098,0.00001603156,0.0008258867,0.8607194,0.0007515798,0.1346981,0.00005945108],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06676836,0.04282387,0.699509,0.002289746,0.00510697,0.002097798,0.02049204,0.01921733,0.1416949],"genre_scores_gemma":[0.06573309,0.06688239,0.5189837,0.003874674,0.001462458,0.00229551,0.04519989,0.004261952,0.2913063],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02626281,"threshold_uncertainty_score":0.0878579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004773801499725451,"score_gpt":0.259770794582647,"score_spread":0.2549969930829215,"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."}}