{"id":"W2039989552","doi":"10.1021/pr0705439","title":"Protein Identification and Peptide Expression Resolver: Harmonizing Protein Identification with Protein Expression Data","year":2007,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Caprion (Canada)","funders":"U.S. Public Health Service","keywords":"Identification (biology); Protein expression; Peptide; Resolver; Biomarker discovery; Proteomics; Bottom-up proteomics; Computational biology; Biology; Biochemistry; Chemistry; Computer science; Tandem mass spectrometry; Gene; Protein mass spectrometry; Mass spectrometry","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":[],"consensus_categories":[],"category_scores_codex":[0.007636316,0.0002929186,0.0003607169,0.0005172678,0.0007147343,0.000368853,0.001434049,0.000276811,0.00007811591],"category_scores_gemma":[0.0008248131,0.0002347542,0.00006467554,0.0006657146,0.0003269231,0.001461022,0.0006726411,0.001732237,0.00001379204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002905575,"about_ca_system_score_gemma":0.0002705531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003126779,"about_ca_topic_score_gemma":0.000008157993,"domain_scores_codex":[0.9951996,0.0001837359,0.001351688,0.0007920905,0.001782741,0.0006901621],"domain_scores_gemma":[0.9953156,0.0001131244,0.001303238,0.001631897,0.001294987,0.0003411376],"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":[0.0006900176,0.0002079034,0.000149214,0.000435568,0.000017737,0.00003569633,0.000159135,0.00000331756,0.9927754,0.0002990102,0.000234866,0.00499214],"study_design_scores_gemma":[0.0007237884,0.0001609228,0.0002305146,0.00229112,0.0000121561,0.00007743415,0.0004958011,0.0001736842,0.9868581,0.004492087,0.004214293,0.0002700923],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8178865,0.0004215157,0.1770039,0.0008120921,0.00001201737,0.003310903,0.00003656196,0.00008725691,0.000429298],"genre_scores_gemma":[0.8189796,0.00006122671,0.1766853,0.000004116954,0.0003366357,0.000823656,0.00005149466,0.00008015336,0.002977787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006811503,"threshold_uncertainty_score":0.9572997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1133103649860695,"score_gpt":0.3881823402315962,"score_spread":0.2748719752455267,"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."}}