{"id":"W2339738230","doi":"10.15252/msb.20156660","title":"Pooled‐matrix protein interaction screens using Barcode Fusion Genetics","year":2016,"lang":"en","type":"article","venue":"Molecular Systems Biology","topic":"Fungal and yeast genetics research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":128,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Lunenfeld-Tanenbaum Research Institute; Ontario Institute for Cancer Research; University of Toronto","funders":"Japan Science and Technology Agency; Canadian Institutes of Health Research; Life Science Foundation of Japan; National Human Genome Research Institute; Nestlé Nutrition Council, Japan; Astellas Foundation for Research on Metabolic Disorders; Krembil Foundation; Canada Excellence Research Chairs, Government of Canada; Japan Society for the Promotion of Science London; Avon Foundation for Women","keywords":"Barcode; Biology; Computational biology; Genetics; Fusion protein; Computer science; Gene; Recombinant DNA","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":[0.0002587654,0.0002563485,0.0002407299,0.000130574,0.0001077891,0.00003596694,0.0003283902,0.0003725345,0.00003115505],"category_scores_gemma":[0.0001078026,0.0001845565,0.0001331406,0.0001295475,0.0001374182,0.000004310686,0.0003329285,0.0001155266,0.00008279357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005183741,"about_ca_system_score_gemma":0.0001089088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001002904,"about_ca_topic_score_gemma":0.0000166541,"domain_scores_codex":[0.9978788,0.0004155141,0.0003694877,0.0006195361,0.0001863969,0.0005302096],"domain_scores_gemma":[0.9988827,0.00001340173,0.0001317043,0.0005870701,0.0002189165,0.0001662114],"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":[0.0000971735,0.0000374667,0.001033743,0.00003097864,0.00007849239,0.00001476372,0.000006379455,0.0002045846,0.9949012,0.0003276826,0.0001145882,0.003152892],"study_design_scores_gemma":[0.0006794253,0.0005610264,0.0001300847,0.00008965364,0.00002386395,0.0001080316,0.00003009716,0.00148026,0.9692002,0.00007622856,0.02729173,0.0003294033],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9078314,0.003198884,0.08732007,0.0001745731,0.0003971593,0.0005541305,0.00005492609,0.00002400246,0.0004448725],"genre_scores_gemma":[0.9971275,0.0001287194,0.0009942566,0.00005501628,0.0003854952,0.00005770961,0.00006561763,0.00005016967,0.001135509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08929612,"threshold_uncertainty_score":0.7525997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02232210647343369,"score_gpt":0.3187864556190539,"score_spread":0.2964643491456203,"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."}}