{"id":"W2954028792","doi":"10.1016/j.drudis.2019.06.020","title":"Target 2035: probing the human proteome","year":2019,"lang":"en","type":"article","venue":"Drug Discovery Today","topic":"Protein Degradation and Inhibitors","field":"Biochemistry, Genetics and Molecular Biology","cited_by":178,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; Structural Genomics Consortium","funders":"Eshelman Institute for Innovation, University of North Carolina at Chapel Hill; Janssen Biotech; Innovative Medicines Initiative; Ontario Genomics Institute; Canada Foundation for Innovation; Wellcome Trust; Merck KGaA; AbbVie; Ontario Ministry of Research, Innovation and Science; MSD Life Science Foundation, Public Interest Incorporated Foundation; Bayer; Pfizer; Fundação de Amparo à Pesquisa do Estado de São Paulo; Boehringer Ingelheim","keywords":"Human proteome project; Proteome; Computational biology; Human disease; Human genome; Drug discovery; Genomics; Function (biology); Biology; Human health; Genome; Relevance (law); Drug development; Data science; Bioinformatics; Proteomics; Genetics; Computer science; Drug; Medicine; Gene; Political science; Pharmacology","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":[0.0002111024,0.0001282524,0.00009431065,0.00002158566,0.0001249664,0.00008744891,0.0002529756,0.00006152382,0.0001184753],"category_scores_gemma":[0.00002392801,0.00008614299,0.00008842206,0.00006944931,0.00005271905,0.00001869595,0.0001319888,0.0001058554,0.0001232343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000122348,"about_ca_system_score_gemma":0.00004862906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001924292,"about_ca_topic_score_gemma":0.000007822694,"domain_scores_codex":[0.9991618,0.0000616952,0.000154568,0.0002788006,0.0001402066,0.0002029606],"domain_scores_gemma":[0.9994227,0.000005252201,0.00007409995,0.0004348817,0.0000283496,0.00003472395],"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":[0.00001772391,0.00004790954,0.003516091,0.00002000945,0.00002658244,7.542047e-7,0.0001117821,0.00007817911,0.973737,0.001680918,0.02060741,0.0001556215],"study_design_scores_gemma":[0.0003239902,0.00006568745,0.001107867,0.0000204551,0.00000452045,0.000002945751,0.0001316468,0.00002151789,0.780995,0.0003360763,0.2167992,0.0001910845],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861217,0.0002241818,0.0002339349,0.00085722,0.000277963,0.0006868085,0.00001522098,0.00001800295,0.01156504],"genre_scores_gemma":[0.9581016,0.000009268351,0.00009058807,0.000533542,0.0002703783,0.00007245596,0.0001517126,0.00001986626,0.04075055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1961918,"threshold_uncertainty_score":0.3512809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005542792617020583,"score_gpt":0.2247918352112931,"score_spread":0.2192490425942726,"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."}}