{"id":"W2790639460","doi":"10.6028/nist.sp.1097","title":"Accelerating innovation in 21st century biosciences :","year":2009,"lang":"en","type":"report","venue":"","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; National Institute of Biomedical Imaging and Bioengineering; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Partenariat Canadien Contre Le Cancer; Agricultural Research Service; University of California, San Francisco; U.S. Forest Service; U.S. Geological Survey; National Centers for Coastal Ocean Science; National Oceanic and Atmospheric Administration; U.S. Food and Drug Administration; National Institutes of Health; United Soybean Board; Johns Hopkins University; Brandeis University; Archer Daniels Midland; Biogen; School of Medicine, Stanford University; National Institute of Standards and Technology; Genentech; U.S. Environmental Protection Agency; Industrial Technology Research Institute; Georgia State University; U.S. Department of Agriculture; University of North Carolina at Chapel Hill; U.S. Department of Energy; National Science Foundation","keywords":"Data science; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0004984327,0.0001359632,0.0002946107,0.0007564771,0.00004889149,0.00001099938,0.0000856104,0.006039388,0.0002284782],"category_scores_gemma":[0.0003245684,0.00009513959,0.00003651939,0.001344306,0.00008067892,0.00004104876,0.00002830655,0.003556924,0.00001669696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000102375,"about_ca_system_score_gemma":0.0007119047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001110722,"about_ca_topic_score_gemma":0.00003857253,"domain_scores_codex":[0.9987459,0.000008893936,0.0004811003,0.0002711762,0.0003027676,0.0001901231],"domain_scores_gemma":[0.999429,0.00001364888,0.0001685616,0.0001860394,0.0001830907,0.00001961935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003651422,0.0004296835,0.01369039,0.0003727855,0.0001066336,0.0003623907,0.0002154929,0.000001597992,0.007257361,0.02746578,0.04107947,0.9089819],"study_design_scores_gemma":[0.0007734226,0.0003981585,0.0408015,0.001503724,0.00008228678,0.0006164815,0.0007017816,0.00006207744,0.00635162,0.000344638,0.9479247,0.0004396303],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02011718,0.002222412,0.00002522329,0.01929675,0.001072481,0.0003285968,0.000001279041,0.0001859547,0.9567501],"genre_scores_gemma":[0.8730311,0.073562,0.003671079,0.00506107,0.0007789054,0.00001699439,0.0002845674,0.00003418872,0.04356009],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.91319,"threshold_uncertainty_score":0.9987419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04812364828302703,"score_gpt":0.3250820017446941,"score_spread":0.2769583534616671,"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."}}