{"id":"W2058794069","doi":"10.1021/ac048152q","title":"Integrated Sample Processing System Involving On-Column Protein Adsorption, Sample Washing, and Enzyme Digestion for Protein Identification by LC−ESI MS/MS","year":2005,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Chromatography; Mass spectrometry; Elution; Sample preparation in mass spectrometry; Electrospray ionization; Digestion (alchemy); Sample preparation; Proteomics; Bottom-up proteomics; Electrospray; Adsorption; Protein purification; Protein mass spectrometry; Biochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001022888,0.001032522,0.001294951,0.0008549409,0.0007401476,0.0009934504,0.00148899,0.001007096,0.004293042],"category_scores_gemma":[0.0005920282,0.0005402525,0.0005222039,0.0004520861,0.0003762075,0.0006156314,0.0006573243,0.001314042,0.002409799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007013799,"about_ca_system_score_gemma":0.001825402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001553635,"about_ca_topic_score_gemma":0.002232405,"domain_scores_codex":[0.9989931,0.00007937981,0.0000603941,0.000291476,0.0004756629,0.0001000694],"domain_scores_gemma":[0.9994988,0.00008212202,0.00004470686,0.00006902623,0.000222115,0.00008325312],"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":[0.0002454198,0.0002630871,0.0004732844,0.0000965944,0.00004168705,0.00004536104,0.00002477156,0.0001924662,0.9762442,0.0001885992,0.000970243,0.02121423],"study_design_scores_gemma":[0.0001890407,0.001281048,0.008430682,0.00002493651,0.000178676,0.0006431212,0.00002934246,0.0148709,0.9530563,0.000289484,0.02092818,0.00007829576],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2186072,0.001725459,0.7562461,0.0003594994,0.0004921092,0.002289976,0.002842391,0.01439345,0.003043724],"genre_scores_gemma":[0.1574108,0.00134905,0.8185083,0.001093693,0.0002262544,0.002984942,0.007435344,0.0005021773,0.01048944],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004293042,"threshold_uncertainty_score":0.01436168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589513148336019,"score_gpt":0.2555341939044049,"score_spread":0.2396390624210447,"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."}}