{"id":"W2888670791","doi":"10.15562/gnc.62","title":"CRISPR as a Versatile Technology for Gene Activation and Genome Editing","year":2018,"lang":"en","type":"article","venue":"Journal of Genes and Cells","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"CRISPR; Genome editing; Zinc finger nuclease; Transcription activator-like effector nuclease; Cas9; Biology; Gene; Genome engineering; Computational biology; Genome; Genetics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009972839,0.00006361362,0.00008788248,0.00005362892,0.00005388705,0.00001407648,0.00004628409,0.00007663955,0.000005422926],"category_scores_gemma":[0.00002209025,0.00005687352,0.00002869448,0.00003252965,0.00004195111,0.000003456713,0.00003281656,0.00003447662,4.45468e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003717592,"about_ca_system_score_gemma":0.00001897104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000170265,"about_ca_topic_score_gemma":0.000001321969,"domain_scores_codex":[0.9996281,0.000004529074,0.0001336101,0.00009169254,0.00004185235,0.0001002577],"domain_scores_gemma":[0.9996958,0.000006603823,0.0000829924,0.00006018987,0.000111989,0.00004242298],"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":[0.00003433386,0.000006844352,0.0001511947,0.00001357281,0.0000262833,6.64196e-7,0.00005019413,0.00002867749,0.991067,0.00001007276,0.000160029,0.008451167],"study_design_scores_gemma":[0.0003525305,0.0006598721,0.0003435451,0.000008340518,0.00001844513,0.00007118534,0.0002377287,0.00006897916,0.9488949,0.0001056965,0.04917723,0.00006157103],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9581533,0.002508787,0.03889326,0.0001631449,0.0001596188,0.00005987283,0.000003166896,0.000002100149,0.00005675771],"genre_scores_gemma":[0.9926223,0.0008516341,0.005380264,0.00006792336,0.0009790821,0.000001864131,0.000002326544,0.00000928489,0.00008537796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0490172,"threshold_uncertainty_score":0.2319235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004981750588696437,"score_gpt":0.2725960604320112,"score_spread":0.2676143098433148,"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."}}