{"id":"W2144861706","doi":"10.1002/smll.201303842","title":"Nanoparticle‐Enabled, Image‐Guided Treatment Planning of Target Specific RNAi Therapeutics in an Orthotopic Prostate Cancer Model","year":2014,"lang":"en","type":"article","venue":"Small","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Small interfering RNA; RNA interference; In vivo; Fluorescence-lifetime imaging microscopy; Context (archaeology); Nanotechnology; Materials science; Fluorescence; Chemistry; RNA; Biology; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0000889709,0.0001291342,0.0001476553,0.0000350083,0.00002523629,0.00001609331,0.0001224403,0.00006923063,0.00001284928],"category_scores_gemma":[0.000003570616,0.0001090814,0.00004642078,0.00004671415,0.00003863632,0.000005968639,0.00002957914,0.00004068527,0.000003305742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002012783,"about_ca_system_score_gemma":0.00005860831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008224834,"about_ca_topic_score_gemma":0.0001684518,"domain_scores_codex":[0.9992164,0.00004506002,0.0002097522,0.0002515867,0.0000561898,0.0002209557],"domain_scores_gemma":[0.9995454,0.000003963186,0.00006594497,0.0002714013,0.00006793115,0.00004538142],"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":[0.0001100417,0.00009635794,0.04813087,0.00001074847,0.00002339603,0.000002741842,0.0003857188,0.01000843,0.9388747,0.00002064703,0.00005849736,0.00227784],"study_design_scores_gemma":[0.0008216705,0.0006234192,0.004075637,0.00002460366,0.00001266515,0.000001770418,0.00009302419,0.01410955,0.9772391,0.0002101624,0.00262631,0.0001620411],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980485,0.0006770872,0.0005905493,0.00005005821,0.00006407132,0.0001559719,0.0000142124,0.000006761484,0.0003927237],"genre_scores_gemma":[0.9970917,0.0003886467,0.001658803,0.0001596984,0.00007142773,0.00004004358,0.0000390031,0.0000160766,0.0005345715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04405523,"threshold_uncertainty_score":0.4448211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0445010758771071,"score_gpt":0.2983823827907504,"score_spread":0.2538813069136432,"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."}}