{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002191669,0.0003668168,0.0002956717,0.0004409111,0.0002394007,0.0003603026,0.0004385179,0.0005947154,0.001591697],"category_scores_gemma":[0.0001759812,0.0001830548,0.0003732199,0.0004001659,0.0002805456,0.0001855025,0.0002897542,0.0007826997,0.0005201244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006633173,"about_ca_system_score_gemma":0.0004539808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002703988,"about_ca_topic_score_gemma":0.003737607,"domain_scores_codex":[0.9997287,0.0000209773,0.00001381828,0.0000650137,0.0001136541,0.00005778342],"domain_scores_gemma":[0.9999347,0.00001124774,0.00001994117,0.000008766258,0.0000117696,0.00001361762],"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":[0.00004811076,0.00001243817,0.00006779544,0.00008857637,0.000008998365,0.00005232923,0.000009771145,0.0001498915,0.9917172,0.0004751782,0.0003012333,0.007068602],"study_design_scores_gemma":[0.00001503298,0.0001072607,0.0007280053,0.000008380216,0.00001731563,0.0003671432,0.000005329965,0.001522084,0.9874005,0.00008375492,0.009731184,0.0000139568],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.683315,0.03995201,0.2436191,0.001104238,0.000579208,0.0008964688,0.003787222,0.00464774,0.02209891],"genre_scores_gemma":[0.9298079,0.007846473,0.0517233,0.0002330582,0.00003497496,0.0001870177,0.00163618,0.0001492321,0.008381892],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002703988,"threshold_uncertainty_score":0.005376458,"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."}}