{"id":"W2748412021","doi":"10.1038/leu.2017.269","title":"RNA interference efficiently targets human leukemia driven by a fusion oncogene in vivo","year":2017,"lang":"en","type":"letter","venue":"Leukemia","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Precision Nanosystems (Canada); University of British Columbia; BC Cancer Agency","funders":"","keywords":"RNA interference; Leukemia; In vivo; RNA; Oncogene; Fusion gene; Oncogene Proteins; Biology; Cancer research; Virology; Computational biology; Fusion; Genetics; Gene; Regulation of gene expression; Cell cycle","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":[0.0007268729,0.0005095748,0.0003499397,0.0002398967,0.0004539188,0.0009476249,0.0003876056,0.002842926,0.001799921],"category_scores_gemma":[0.0007963068,0.0002084376,0.0003035268,0.0001778079,0.0008095996,0.000397006,0.0003438993,0.002572081,0.001299614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008317204,"about_ca_system_score_gemma":0.0003821919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004229935,"about_ca_topic_score_gemma":0.0006861871,"domain_scores_codex":[0.9996082,0.0000848091,0.0000263046,0.00004299904,0.0001453756,0.00009228355],"domain_scores_gemma":[0.9996879,0.0001868038,0.00003556686,0.00003341988,0.00002947607,0.00002697159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001669152,0.0004557999,0.001986274,0.0003111403,0.00007028991,0.009612446,0.0002560266,0.001046987,0.7910261,0.03152624,0.0897648,0.07227484],"study_design_scores_gemma":[0.0004703001,0.0007695878,0.001846065,0.00004563887,0.00008788444,0.006860583,0.0001188129,0.004249383,0.6389525,0.007962598,0.3385995,0.00003715084],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3408726,0.03315763,0.05131962,0.4308411,0.01739386,0.0005389749,0.001040012,0.002785839,0.1220504],"genre_scores_gemma":[0.846906,0.0157613,0.01597365,0.05440934,0.005502726,0.0003527442,0.0006865452,0.000311755,0.06009601],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002842926,"threshold_uncertainty_score":0.006034613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01306351804502774,"score_gpt":0.2583927460120305,"score_spread":0.2453292279670028,"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."}}