{"id":"W2118290743","doi":"10.1093/bioinformatics/btp366","title":"Automated protein (re)sequencing with MS/MS and a homologous database yields almost full coverage and accuracy","year":2009,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bioinformatics Solutions (Canada); University of Waterloo; Western University","funders":"","keywords":"Protein sequencing; Sequence database; Sequence (biology); Proteomics; Protein methods; Computational biology; DNA sequencing; Tandem mass spectrometry; Database; Peptide sequence; Computer science; Sequence analysis; Mass spectrometry; Biology; Genetics; DNA; Chemistry; Gene; Chromatography","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":[0.00329236,0.0009401812,0.001413977,0.00192465,0.0004420038,0.001048882,0.001184222,0.001083932,0.004421204],"category_scores_gemma":[0.006689619,0.0004666432,0.0006505318,0.001441674,0.0005396221,0.001249368,0.0009430409,0.000657654,0.006609351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004062502,"about_ca_system_score_gemma":0.0006825191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008831418,"about_ca_topic_score_gemma":0.001182774,"domain_scores_codex":[0.9970259,0.0006809147,0.0002747651,0.000860271,0.001040771,0.000117366],"domain_scores_gemma":[0.9948619,0.001533736,0.0007214429,0.001518129,0.001227561,0.0001371649],"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":[0.000638295,0.0002042326,0.005456053,0.0004892976,0.0001343824,0.0003496844,0.0001092191,0.003506913,0.80209,0.001073262,0.00835232,0.1775963],"study_design_scores_gemma":[0.000169319,0.0003315302,0.01392201,0.0000951932,0.0001898219,0.002697606,0.00009577398,0.07352851,0.8689689,0.003394691,0.03651144,0.00009520011],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3302896,0.002184876,0.6267383,0.0009162183,0.0001907005,0.0003331168,0.008112377,0.02097422,0.01026066],"genre_scores_gemma":[0.2508649,0.0005318244,0.7296687,0.0004596928,0.00006964033,0.0002397886,0.01209976,0.001660355,0.004405342],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004421204,"threshold_uncertainty_score":0.01741189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0146431126850085,"score_gpt":0.2623744513277079,"score_spread":0.2477313386426994,"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."}}