{"id":"W2030659385","doi":"10.1142/s0219720006001746","title":"PRIMA: PEPTIDE ROBUST IDENTIFICATION FROM MS/MS SPECTRA","year":2006,"lang":"en","type":"article","venue":"Journal of Bioinformatics and Computational Biology","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Western University; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tandem mass spectrometry; Mascot; Computer science; Identification (biology); Software; Construct (python library); Ion trap; Proteomics; Peptide; Tandem; Artificial intelligence; Mass spectrometry; Data mining; Chemistry; Chromatography; Biology; Engineering","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":[0.003547044,0.001739676,0.001415384,0.001775605,0.0008024761,0.002286159,0.002638323,0.0009449981,0.004516404],"category_scores_gemma":[0.008112245,0.0009078727,0.001398172,0.001475642,0.0007575037,0.002032873,0.003123647,0.001923766,0.00658682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003456845,"about_ca_system_score_gemma":0.001164584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005921571,"about_ca_topic_score_gemma":0.000714606,"domain_scores_codex":[0.9983087,0.0003891363,0.000133672,0.0003938383,0.0006888355,0.00008590656],"domain_scores_gemma":[0.9971691,0.0008783346,0.0004365464,0.0008495252,0.0005380921,0.0001284661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000879317,0.0002543083,0.005102648,0.000950413,0.0003994399,0.0006574877,0.000151083,0.03965214,0.1029876,0.009404259,0.02108561,0.8184757],"study_design_scores_gemma":[0.00006066117,0.0003053642,0.002311174,0.00005019434,0.00007739955,0.001427295,0.00004361634,0.8394868,0.119656,0.01663113,0.01984024,0.0001101535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009308604,0.0004057371,0.9633088,0.0001186056,0.00006582287,0.000133058,0.0005779896,0.02541764,0.0006637897],"genre_scores_gemma":[0.07289635,0.00039409,0.9192401,0.000172517,0.00007473224,0.0002642375,0.002332216,0.001936337,0.002689401],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004516404,"threshold_uncertainty_score":0.01875877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009623334375525457,"score_gpt":0.2478373714365536,"score_spread":0.2382140370610281,"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."}}