{"id":"W3097045341","doi":"10.1039/d0cc06241c","title":"ZIF-C for targeted RNA interference and CRISPR/Cas9 based gene editing in prostate cancer","year":2020,"lang":"en","type":"article","venue":"Chemical Communications","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"Microsemi (Canada)","funders":"Commonwealth Scientific and Industrial Research Organisation","keywords":"CRISPR; Gene knockdown; RNA interference; Cas9; Prostate cancer; Gene; CRISPR interference; RNA; Cancer; Cancer research; Genome editing; Gene expression; Computational biology; Chemistry; Biology; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005847258,0.0000966407,0.0001086127,0.00001738273,0.00005423887,0.00002041045,0.0003890485,0.0000670675,0.000007341381],"category_scores_gemma":[0.000180419,0.00008947516,0.00003966012,0.0000761487,0.0001020402,0.000005233419,0.0002568101,0.0001273745,0.000001863246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001294848,"about_ca_system_score_gemma":0.0000530577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003010467,"about_ca_topic_score_gemma":0.00004404989,"domain_scores_codex":[0.9993863,0.00002788035,0.0001812242,0.0002197698,0.00003636536,0.0001484804],"domain_scores_gemma":[0.9993643,0.00003578443,0.00005253206,0.0003794388,0.00009193603,0.00007605914],"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":[0.00005805499,0.00002772243,0.000999385,0.00002149562,0.00001150215,2.221516e-7,0.0001322857,0.00001235592,0.9950191,0.00001325723,0.001448709,0.002255904],"study_design_scores_gemma":[0.0004429401,0.00007580237,0.0001759329,0.00003071687,0.00001039277,6.993228e-7,0.0001136963,0.00482122,0.9874089,0.00005487966,0.006739917,0.0001249379],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854559,0.002516138,0.002260744,0.00907056,0.00003548016,0.0002907148,0.0001350182,0.00001680505,0.000218585],"genre_scores_gemma":[0.9932567,0.0005043117,0.004161051,0.001404936,0.0000848512,0.0001955021,0.0003493361,0.00001247503,0.00003080078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007800781,"threshold_uncertainty_score":0.3648691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03941455429867655,"score_gpt":0.3067755534147817,"score_spread":0.2673609991161052,"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."}}