{"id":"W1961449438","doi":"10.1534/genetics.115.180208","title":"The Transgenic RNAi Project at Harvard Medical School: Resources and Validation","year":2015,"lang":"en","type":"article","venue":"Genetics","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":721,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; Cancer Research UK; NIH Office of the Director; National Key Research and Development Program of China; Ministry of Science and Technology of the People's Republic of China; National Natural Science Foundation of China; National Institute of General Medical Sciences; School of Medicine, New York University; Institute of Genetics; National Institutes of Health; Yale University; Cold Spring Harbor Laboratory; York University; Howard Hughes Medical Institute","keywords":"RNA interference; Biology; Genetics; Computational biology; Stock (firearms); Phenotype; Genome; Gene; Engineering; RNA","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0150447,0.001370962,0.00202675,0.005497387,0.002662767,0.001715639,0.003340211,0.001285241,0.0317258],"category_scores_gemma":[0.009174723,0.001328248,0.0009237772,0.00358098,0.001083778,0.001495994,0.003466303,0.002426719,0.03583205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001568041,"about_ca_system_score_gemma":0.007389226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00591298,"about_ca_topic_score_gemma":0.006383646,"domain_scores_codex":[0.9944481,0.0009799828,0.000624621,0.0006694684,0.002770049,0.0005077475],"domain_scores_gemma":[0.9892686,0.0008595646,0.0005867712,0.003317571,0.004303132,0.001664289],"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":[0.002060186,0.0006823726,0.008216229,0.001269981,0.0002287171,0.0007497246,0.0007064992,0.001156633,0.4914555,0.01050609,0.2836274,0.1993407],"study_design_scores_gemma":[0.001088671,0.001141842,0.02003829,0.0006112525,0.0003562692,0.001583791,0.0001516977,0.003349479,0.1806328,0.002806604,0.7880526,0.0001866869],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06143578,0.005247128,0.4768293,0.004055293,0.001839206,0.0207766,0.3407058,0.03548793,0.05362295],"genre_scores_gemma":[0.03920556,0.004104587,0.3209876,0.001991031,0.0002800966,0.02193216,0.5663331,0.008577886,0.03658804],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0317258,"threshold_uncertainty_score":0.1061333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01649252059750513,"score_gpt":0.3041229774277539,"score_spread":0.2876304568302488,"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."}}