{"id":"W4327654335","doi":"10.1039/d2md00441k","title":"Target 2035 – an update on private sector contributions","year":2023,"lang":"en","type":"editorial","venue":"RSC Medicinal Chemistry","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Structural Genomics Consortium; University of Toronto","funders":"Eshelman Institute for Innovation, University of North Carolina at Chapel Hill; Pharmaceuticals Bayer; Horizon 2020 Framework Programme; Genentech; Innovative Medicines Initiative; Ontario Institute for Cancer Research; European Commission; EMD Serono; Kungliga Tekniska Högskolan; Canada Foundation for Innovation; Ontario Genomics Institute; Takeda Pharmaceutical Company; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; Janssen Research and Development; Ontario Genomics; Genome Canada; Diamond Light Source; Boehringer Ingelheim; McGill University; Pfizer","keywords":"Private sector; Public sector; Political science; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001472388,0.0005564839,0.0006757813,0.0001196479,0.0002165639,0.0002126395,0.002372962,0.0007656357,0.0001799893],"category_scores_gemma":[0.003529278,0.0005391473,0.0001933431,0.0006394506,0.0001423567,0.0002895224,0.0005337541,0.001739316,0.0003214201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004791885,"about_ca_system_score_gemma":0.001251794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002222798,"about_ca_topic_score_gemma":0.00000152152,"domain_scores_codex":[0.9949815,0.0002368997,0.0005954304,0.001252708,0.002239097,0.0006943434],"domain_scores_gemma":[0.9944138,0.002924019,0.0003785258,0.00134892,0.0004217915,0.0005129275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003616411,0.00009034623,0.000001833737,0.0001853868,0.00008300457,0.0001817168,0.0000515856,0.001245938,0.0007117772,0.0009604868,0.9958555,0.0005962922],"study_design_scores_gemma":[0.0007697212,0.0001295478,0.00002675533,0.0003711896,0.00005566706,0.00001096558,0.000009502292,0.01798321,0.006438034,0.008863004,0.9646821,0.0006602986],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0005940807,0.000190789,0.1079169,0.001393057,0.886282,0.0002349541,0.001183063,0.0007765474,0.001428558],"genre_scores_gemma":[0.0006386366,0.00009247122,0.01165679,0.0003008416,0.9805798,0.00009907986,0.004744636,0.0001072375,0.001780525],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.09626013,"threshold_uncertainty_score":0.999706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01466746171797393,"score_gpt":0.3220159014091742,"score_spread":0.3073484396912003,"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."}}