{"id":"W2008317045","doi":"10.1021/ac001196o","title":"Implementation and Uses of Automated de Novo Peptide Sequencing by Tandem Mass Spectrometry","year":2001,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":292,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research & Development Corporation","funders":"","keywords":"Chemistry; Tandem mass spectrometry; Sequence database; Mass spectrometry; Database; Isobaric labeling; Computational biology; Database search engine; Peptide mass fingerprinting; Tandem; False positive paradox; Computer science; Search engine; Protein mass spectrometry; Chromatography; Information retrieval; Proteomics; Artificial intelligence; Biochemistry","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":[0.001925088,0.0005182429,0.0005869399,0.0009051563,0.000538799,0.001262221,0.001783657,0.0004706247,0.002803426],"category_scores_gemma":[0.002995384,0.0005161481,0.0004746533,0.0007888377,0.0003186517,0.001032625,0.0009034869,0.001012367,0.001654404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005390155,"about_ca_system_score_gemma":0.001162346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001608517,"about_ca_topic_score_gemma":0.001238165,"domain_scores_codex":[0.9989401,0.0001366241,0.0001131466,0.0003140207,0.0003873303,0.0001088556],"domain_scores_gemma":[0.998611,0.0003491376,0.00009129643,0.0004026824,0.0004611593,0.00008465245],"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":[0.001509339,0.0008133677,0.009736539,0.0004902228,0.0001644396,0.0006917319,0.0006563842,0.0203277,0.3568566,0.009609792,0.007538771,0.5916051],"study_design_scores_gemma":[0.0003004195,0.0008299865,0.008412411,0.0001345108,0.00009816601,0.001314546,0.0001268513,0.2629902,0.6152542,0.004238378,0.1060908,0.0002096356],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06939179,0.0003337889,0.8856142,0.000188967,0.0000927313,0.0006009006,0.001074734,0.03718757,0.005515317],"genre_scores_gemma":[0.09644704,0.0003152546,0.8958601,0.0001215467,0.00002188638,0.0004129658,0.003052037,0.001053283,0.002715811],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002803426,"threshold_uncertainty_score":0.01018095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0148378484794838,"score_gpt":0.318572588763185,"score_spread":0.3037347402837012,"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."}}