{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001111658,0.001494941,0.001010502,0.0009839498,0.0005226957,0.001010571,0.001077596,0.0009667709,0.002492441],"category_scores_gemma":[0.0009291486,0.0005543066,0.0009436219,0.0008500557,0.0005942262,0.000618096,0.001655046,0.001311808,0.001658324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006646924,"about_ca_system_score_gemma":0.0004167135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001322677,"about_ca_topic_score_gemma":0.003250875,"domain_scores_codex":[0.9976369,0.0003013935,0.0001680119,0.0004715984,0.001137892,0.0002840959],"domain_scores_gemma":[0.9989781,0.0003125785,0.0002320931,0.0001612629,0.0001781492,0.0001377847],"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":[0.00004443398,0.00003519935,0.0001181964,0.00003990957,0.0000213994,0.00002867224,0.00001486852,0.0001260813,0.9982186,0.00009069996,0.00008988375,0.001172001],"study_design_scores_gemma":[0.000009223401,0.00016638,0.001042646,0.000003750647,0.00001915388,0.0001307246,0.00001425512,0.001411353,0.9954174,0.0000705031,0.001700868,0.00001385985],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.725218,0.001351988,0.258993,0.0004741404,0.0001825877,0.0009008048,0.003656846,0.004479799,0.004742851],"genre_scores_gemma":[0.7863862,0.001386166,0.1936689,0.0003854553,0.00003741949,0.0008275748,0.006801974,0.001322837,0.009183536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002492441,"threshold_uncertainty_score":0.008337975,"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."}}