{"id":"W87556421","doi":"10.1007/978-1-60761-842-3_11","title":"Mass Spectrometric Protein Identification Using the Global Proteome Machine","year":2010,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Center for Research Resources","keywords":"Proteome; Identification (biology); Mass spectrometry; Computational biology; Computer science; Cover (algebra); Chemistry; Biology; Bioinformatics; Chromatography; Engineering; Ecology","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":[0.002005981,0.001512679,0.001626543,0.003250271,0.0005208878,0.001323976,0.0008290345,0.0006963999,0.00158674],"category_scores_gemma":[0.002775664,0.000354749,0.0008232865,0.002438301,0.0005354882,0.001730957,0.001464287,0.001103461,0.002057245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003310141,"about_ca_system_score_gemma":0.0003023692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001347623,"about_ca_topic_score_gemma":0.0001439832,"domain_scores_codex":[0.9986647,0.0003317071,0.0001090512,0.0004081489,0.0004171596,0.00006922576],"domain_scores_gemma":[0.9990456,0.0003382429,0.0001327783,0.0002346988,0.0001958688,0.00005281208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006580608,0.000118428,0.005383931,0.0009536518,0.0002797617,0.0005590714,0.0002352733,0.009101531,0.4583849,0.01238148,0.01201118,0.4999326],"study_design_scores_gemma":[0.00009625691,0.0007165842,0.01333499,0.0001248652,0.0001800837,0.003117444,0.0002080171,0.320533,0.5397254,0.04806537,0.07369988,0.0001981176],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02812564,0.001123975,0.9544921,0.0001926259,0.0001141984,0.0001420278,0.002027133,0.01181071,0.001971598],"genre_scores_gemma":[0.1245511,0.001121444,0.8674791,0.0001988305,0.00008847217,0.0003643609,0.003920902,0.0006762127,0.001599489],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003250271,"threshold_uncertainty_score":0.01060873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01940846136681085,"score_gpt":0.4109472254160365,"score_spread":0.3915387640492256,"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."}}