{"id":"W1996792890","doi":"10.1385/mb:22:3:301","title":"Searching Sequence Databases via De Novo Peptide Sequencing by Tandem Mass Spectrometry","year":2002,"lang":"en","type":"article","venue":"Molecular Biotechnology","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":96,"is_retracted":false,"has_abstract":false,"ca_institutions":"Research & Development Corporation","funders":"","keywords":"Sequence database; Sequence (biology); Tandem mass spectrometry; Database; Computational biology; Mass spectrometry; Peptide sequence; Computer science; Peptide; Sequence analysis; Biology; Chemistry; Genetics; DNA; Biochemistry; Chromatography; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001055154,0.0002173015,0.0001997083,0.0001300343,0.0001666867,0.00002417258,0.0005381285,0.0003178506,0.0003359578],"category_scores_gemma":[0.00009653332,0.0002469258,0.00007032813,0.0003093003,0.0002219904,0.00007065188,0.0001895193,0.0007478673,0.00004399923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003703584,"about_ca_system_score_gemma":0.0000260061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008243,"about_ca_topic_score_gemma":0.00000541262,"domain_scores_codex":[0.9985014,0.00001726314,0.0002365331,0.000525754,0.000153383,0.0005656428],"domain_scores_gemma":[0.9989163,0.00003331853,0.0001072356,0.0008264934,0.00002584584,0.00009077194],"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":[0.000001552482,0.0000239252,0.0001013436,0.00002019414,0.00001756743,0.0001165495,0.0000152041,0.00003028994,0.989491,0.006761247,0.0001304979,0.003290612],"study_design_scores_gemma":[0.000134067,0.00002038431,5.381369e-7,0.00002838731,0.000009714989,0.0002747239,0.0000463026,0.003043025,0.9779618,0.009501597,0.008719327,0.0002601351],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2754851,0.0004925804,0.719363,0.00149156,0.000006757014,0.0001093083,0.00005449446,0.0006550184,0.002342143],"genre_scores_gemma":[0.6898534,0.000331513,0.3091186,0.000238842,0.00002108675,0.00007679935,0.00004964273,0.000043142,0.0002669757],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4143683,"threshold_uncertainty_score":0.9999983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02333560432786018,"score_gpt":0.280326696736767,"score_spread":0.2569910924089068,"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."}}