{"id":"W4412188000","doi":"10.1002/pmic.70010","title":"Optimizing Proximity Proteomics on the EvoSep‐timsTOF LC–MS System","year":2025,"lang":"en","type":"article","venue":"PROTEOMICS","topic":"Biotin and Related Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Government of Ontario; Ontario Genomics; Genome Canada","keywords":"Biotinylation; Streptavidin; Biotin; Proteomics; Chromatography; Mass spectrometry; Chemistry; Throughput; Computational biology; Computer science; Biology; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003764453,0.0002242204,0.0002044709,0.00004246508,0.0003772075,0.00005031831,0.0003326328,0.0003077141,0.00000325653],"category_scores_gemma":[0.0001389285,0.0001476134,0.0001308312,0.0001461222,0.0001409652,0.000003041077,0.0002494671,0.0003372614,0.00002030795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006061628,"about_ca_system_score_gemma":0.000101171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001286638,"about_ca_topic_score_gemma":0.000005259506,"domain_scores_codex":[0.9988363,0.00009923165,0.0002521189,0.0003933521,0.000117599,0.0003013321],"domain_scores_gemma":[0.999221,0.00002120258,0.0001098115,0.0005079918,0.00009906693,0.0000409781],"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":[0.000659775,0.000354387,0.001218204,0.0005820923,0.001111167,0.000009687506,0.0005168114,0.001348607,0.9288617,0.0442455,0.01839542,0.002696611],"study_design_scores_gemma":[0.0006668371,0.0002250718,0.000156494,0.0003400003,0.00005483655,0.00000945342,0.000387539,0.001382975,0.9805276,0.0002013239,0.01572439,0.0003234478],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8845588,0.004537078,0.03053019,0.007326848,0.001350327,0.006664722,0.00005275853,0.0002174784,0.06476182],"genre_scores_gemma":[0.98188,0.0003968505,0.01315133,0.000783283,0.0002441779,0.0004438451,0.00002074006,0.00003575518,0.003044005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09732124,"threshold_uncertainty_score":0.6019498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00850211522708758,"score_gpt":0.2277108526554297,"score_spread":0.2192087374283421,"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."}}