{"id":"W2137075120","doi":"10.1534/g3.113.006437","title":"Miniature Short Hairpin RNA Screens to Characterize Antiproliferative Drugs","year":2013,"lang":"en","type":"article","venue":"G3 Genes Genomes Genetics","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Toronto","funders":"National Human Genome Research Institute; National Institutes of Health","keywords":"RNA interference; Computational biology; Drug discovery; Phenotypic screening; Biology; Small hairpin RNA; Small molecule; Drug; Mechanism of action; Cell biology; Gene; RNA; Phenotype; Bioinformatics; Pharmacology; Genetics; In vitro","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000629045,0.0007667157,0.0007085263,0.0009293034,0.000220987,0.000717206,0.0004955775,0.0005331417,0.002382778],"category_scores_gemma":[0.0005671116,0.0003957668,0.0005567762,0.0004049951,0.0003504192,0.0002684084,0.0004572259,0.001040882,0.0009560497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004045144,"about_ca_system_score_gemma":0.0002763512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002443991,"about_ca_topic_score_gemma":0.001140597,"domain_scores_codex":[0.999496,0.00009110325,0.00004830997,0.00009072505,0.00022583,0.00004816676],"domain_scores_gemma":[0.9995548,0.000192329,0.00009878237,0.00005821949,0.00005669615,0.00003916194],"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":[0.00003312691,0.00005214796,0.0001391768,0.00003932605,0.00001420746,0.00003737221,0.00001023147,0.0002936297,0.9958904,0.0001424368,0.00009756244,0.003250386],"study_design_scores_gemma":[0.0000517114,0.001074098,0.003120562,0.000007928558,0.00006642085,0.0002507785,0.00001819051,0.003467163,0.9854919,0.0002363458,0.006199133,0.00001584204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7776337,0.003358669,0.1905391,0.000564886,0.0002134602,0.003776255,0.00937918,0.003377682,0.01115703],"genre_scores_gemma":[0.7868696,0.002777471,0.1904064,0.0005345849,0.00008495293,0.002342414,0.005971135,0.0003763368,0.01063719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002382778,"threshold_uncertainty_score":0.007971227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01418543110270847,"score_gpt":0.2434935684027029,"score_spread":0.2293081372999944,"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."}}