{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006136698,0.0005531515,0.0002952095,0.000532972,0.0005060695,0.0005232672,0.0004096828,0.001057817,0.004833138],"category_scores_gemma":[0.0003268107,0.0002261019,0.0003452483,0.0005225619,0.0002648927,0.0003983585,0.0006374427,0.0009742243,0.00267662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004140877,"about_ca_system_score_gemma":0.0005004716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008999294,"about_ca_topic_score_gemma":0.00134756,"domain_scores_codex":[0.9996657,0.0000649319,0.00001030961,0.00006930453,0.0001454589,0.00004417877],"domain_scores_gemma":[0.9999036,0.00001825947,0.000009969244,0.00001246545,0.00002571461,0.00002992136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003771384,0.00006380084,0.0007364257,0.0002769678,0.00002981933,0.0001799459,0.00004731912,0.000209962,0.9414581,0.002148322,0.02306882,0.03140344],"study_design_scores_gemma":[0.0001035399,0.0006498264,0.004934239,0.00004644142,0.00004567639,0.002499127,0.00005397079,0.002695936,0.8217371,0.001714379,0.1654908,0.00002907738],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.4260568,0.05575721,0.2911822,0.0248893,0.002883206,0.001086058,0.03262842,0.01046251,0.1550543],"genre_scores_gemma":[0.588789,0.02938037,0.2261746,0.01666574,0.0006944205,0.001271497,0.04718912,0.001118628,0.08871656],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004833138,"threshold_uncertainty_score":0.01616842,"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."}}