{"id":"W2169240844","doi":"10.1586/14789450.4.3.351","title":"Computational prediction of proteotypic peptides","year":2007,"lang":"en","type":"letter","venue":"Expert Review of Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Theoretical Astrophysics","keywords":"Proteomics; Bottom-up proteomics; Computational biology; Peptide; Chemistry; Mass spectrometry; Quantitative proteomics; Biochemistry; Tandem mass spectrometry; Biology; Chromatography; Protein mass spectrometry; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003036883,0.0003699822,0.0008339508,0.0001021407,0.00005706349,0.000007632932,0.0005199764,0.0006449417,0.0003767027],"category_scores_gemma":[0.0001178263,0.0003529727,0.0003527093,0.0001926789,0.0002028754,0.00007606977,0.0001120051,0.001104107,0.000008704133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001344242,"about_ca_system_score_gemma":0.0002164011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001815324,"about_ca_topic_score_gemma":2.453685e-7,"domain_scores_codex":[0.997479,0.00002838408,0.001285827,0.0004461917,0.0004946387,0.0002660055],"domain_scores_gemma":[0.9973279,0.00009118506,0.001353268,0.0007452773,0.0004391325,0.00004323003],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002920251,0.0001259495,0.00002970152,0.05478305,0.0001209957,0.000008555199,0.00006402803,0.00002379771,0.05552601,0.0007297416,0.8852254,0.003333638],"study_design_scores_gemma":[0.0002189574,0.00007055668,0.000002581961,0.02477678,0.00006609222,0.00003217202,0.000006990279,0.0001428476,0.2129504,0.005483638,0.7558472,0.0004018161],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002244255,0.08607262,0.7174728,0.1737831,0.000196229,0.008253373,0.002171351,0.0004861588,0.01133997],"genre_scores_gemma":[0.00002683142,0.03344052,0.8838431,0.07664772,0.001497556,0.001774753,0.002000028,0.0001065529,0.0006628967],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1663703,"threshold_uncertainty_score":0.9998922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02107778764928412,"score_gpt":0.3177761640914966,"score_spread":0.2966983764422125,"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."}}