{"id":"W4409382497","doi":"10.1016/j.drudis.2025.104359","title":"Advancing ocular gene therapy: a machine learning approach to enhance delivery, uptake and gene expression","year":2025,"lang":"en","type":"review","venue":"Drug Discovery Today","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Paul University","funders":"","keywords":"Genetic enhancement; Gene expression; Gene delivery; Gene; Computational biology; Bioinformatics; Pharmacology; 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":[0.0004681875,0.0007757653,0.0008526938,0.001272326,0.0001293825,0.0007888107,0.0007110094,0.00104187,0.00135797],"category_scores_gemma":[0.0004441531,0.000230269,0.0006777191,0.001194591,0.0003057888,0.0008186942,0.0004264605,0.001291039,0.0008901512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005539403,"about_ca_system_score_gemma":0.0005557053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009957763,"about_ca_topic_score_gemma":0.001039336,"domain_scores_codex":[0.999874,0.00002927002,0.000009625054,0.00002740741,0.00004782719,0.0000119065],"domain_scores_gemma":[0.9998547,0.00007868211,0.00001820322,0.000005673054,0.00003418924,0.000008513826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003839661,0.0001381613,0.0003650481,0.006689454,0.0001527608,0.0001554074,0.00004125197,0.006325465,0.00602848,0.0115855,0.007671311,0.9608089],"study_design_scores_gemma":[0.00004808957,0.0008492929,0.003147451,0.004205532,0.00060607,0.002327156,0.0001007347,0.03433511,0.01616732,0.02687974,0.9111641,0.0001694727],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001536994,0.9686435,0.02338305,0.0008796855,0.0003576709,0.000037821,0.0000505919,0.00008528004,0.005025335],"genre_scores_gemma":[0.01913471,0.9621567,0.01379993,0.0004664069,0.0003595037,0.00006777406,0.000114745,0.00001482005,0.003885387],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00135797,"threshold_uncertainty_score":0.004542887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01086574921384349,"score_gpt":0.2809636186626168,"score_spread":0.2700978694487733,"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."}}