{"id":"W2140572608","doi":"10.1186/1471-2105-11-s1-s4","title":"Better score function for peptide identification with ETD MS/MS spectra","year":2010,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Bioinformatics Solutions (Canada); University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Electron-transfer dissociation; Tandem mass spectrometry; Proteomics; Peptide; Mass spectrometry; Database search engine; Computer science; Computational biology; Tandem mass tag; Bioinformatics; Chemistry; Chromatography; Quantitative proteomics; Search engine; Biology; Information retrieval; 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":[0.005128999,0.00173743,0.001183909,0.003571892,0.0006951278,0.001696296,0.001761227,0.001756944,0.002932884],"category_scores_gemma":[0.01291652,0.0002751878,0.001070734,0.002122467,0.0005840075,0.002648697,0.001361873,0.001147922,0.001598986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001412388,"about_ca_system_score_gemma":0.0009412903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001882475,"about_ca_topic_score_gemma":0.001255063,"domain_scores_codex":[0.9968976,0.0007025326,0.0004064923,0.0003570786,0.001461666,0.0001745205],"domain_scores_gemma":[0.9918478,0.002518424,0.0006137245,0.0006662415,0.004011535,0.0003421918],"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":[0.002061853,0.001102646,0.040924,0.0005763105,0.0004680713,0.0007808632,0.0003324917,0.1639438,0.1375837,0.01019974,0.01353871,0.6284878],"study_design_scores_gemma":[0.00007999951,0.0002465324,0.006018678,0.000015828,0.00005671809,0.0003976871,0.00003705783,0.9200341,0.0657472,0.00338018,0.003889296,0.00009682748],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09914156,0.0002127155,0.8921155,0.0002454299,0.00009429627,0.0001417919,0.0005106013,0.006469924,0.001068293],"genre_scores_gemma":[0.3224028,0.0001365628,0.6717152,0.0001691312,0.00005550199,0.0002762724,0.002586301,0.0007924794,0.001865681],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005128999,"threshold_uncertainty_score":0.02712506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01536811295687333,"score_gpt":0.2511999830844915,"score_spread":0.2358318701276182,"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."}}