{"id":"W4413843081","doi":"10.1101/2025.08.29.668156","title":"Benchmarking of proximity-dependent biotinylation enzymes across cellular compartments and time windows","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Biotin and Related Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Terry Fox Research Institute; University of Toronto; Government of Ontario; Canada Research Chairs; Canadian Institutes of Health Research","keywords":"Biotinylation; Benchmarking; Enzyme; Chemistry; Compartment (ship); Cell biology; Computational biology; Computer science; Biochemistry; Biology; Business","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":[0.001757179,0.0005512586,0.0005755731,0.0005567104,0.0003018573,0.001099381,0.0005483245,0.0005695728,0.0008161375],"category_scores_gemma":[0.001870324,0.0002653998,0.0003412272,0.0008982089,0.0004309219,0.0005140814,0.0009897179,0.0005792428,0.0005593286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007127717,"about_ca_system_score_gemma":0.0003321242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001646513,"about_ca_topic_score_gemma":0.001761004,"domain_scores_codex":[0.9987466,0.0002484307,0.0001663404,0.0003369121,0.0003787928,0.0001227802],"domain_scores_gemma":[0.9992673,0.0002034605,0.0001071431,0.0001320567,0.0002081833,0.00008189341],"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":[0.0002311894,0.00003885922,0.001033402,0.0001226936,0.00002264774,0.00003025254,0.00004860295,0.0008478893,0.9924917,0.0002060796,0.000112893,0.004813911],"study_design_scores_gemma":[0.000005842253,0.0001962541,0.001452264,0.00000781747,0.0000162755,0.00008255276,0.00003061221,0.002379587,0.994046,0.00006604794,0.001706687,0.00001012892],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9507353,0.001949929,0.0434339,0.0001228598,0.0000422565,0.0001406616,0.001428353,0.0005210004,0.001625643],"genre_scores_gemma":[0.903468,0.002374162,0.08536445,0.0001086104,0.00001348218,0.0003089746,0.004580994,0.0003291292,0.003452319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001757179,"threshold_uncertainty_score":0.00929296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008770937196043748,"score_gpt":0.2287010806241629,"score_spread":0.2199301434281192,"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."}}