{"id":"W2326414500","doi":"10.1021/pr200153k","title":"PeaksPTM: Mass Spectrometry-Based Identification of Peptides with Unspecified Modifications","year":2011,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":179,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bioinformatics Solutions (Canada); University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Identification (biology); Tandem mass spectrometry; Database search engine; Mass spectrometry; Sequence (biology); Software; Posttranslational modification; Data mining; Computational biology; Combinatorial chemistry; Chemistry; Information retrieval; Search engine; Chromatography; Programming language; Biochemistry; Biology","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":[0.001996812,0.002099188,0.00120311,0.003328239,0.0008129915,0.001742666,0.002005279,0.001310902,0.005031041],"category_scores_gemma":[0.002761345,0.0006444394,0.001285034,0.001930147,0.000594389,0.00194751,0.001617018,0.001164202,0.003602554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004295355,"about_ca_system_score_gemma":0.001026115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003356689,"about_ca_topic_score_gemma":0.0004681002,"domain_scores_codex":[0.9991196,0.0001047418,0.00008274858,0.0002714702,0.0003493266,0.00007206813],"domain_scores_gemma":[0.9991346,0.0004245788,0.0001744137,0.0001074985,0.0001054206,0.0000536089],"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":[0.002707718,0.0003032797,0.008408058,0.002147428,0.0005232039,0.001495672,0.0002485755,0.006742541,0.4415805,0.006396898,0.02443086,0.5050153],"study_design_scores_gemma":[0.0003018529,0.0005404904,0.007156177,0.00009405079,0.00021802,0.004697952,0.00009543799,0.1834336,0.7478017,0.008821969,0.04661708,0.0002216893],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06182419,0.001986381,0.8698906,0.0002604131,0.0002048502,0.0004198393,0.005764916,0.05649214,0.003156724],"genre_scores_gemma":[0.06279217,0.0005949687,0.9263608,0.0001755612,0.00004300178,0.0004232572,0.005276669,0.001974066,0.002359464],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005031041,"threshold_uncertainty_score":0.01683056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1126874813581207,"score_gpt":0.3659287734738018,"score_spread":0.253241292115681,"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."}}