{"id":"W4376133442","doi":"10.1093/nar/gkad375","title":"OnTarget: <i>in silico</i> design of MiniPromoters for targeted delivery of expression","year":2023,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; BC Children's Hospital; University of British Columbia","funders":"Canadian Institutes of Health Research; Weston Brain Institute; Genome Canada","keywords":"Biology; Enhancer; Computational biology; Promoter; In silico; Chromatin; Bioinformatics; Gene; Gene expression; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001098576,0.001076825,0.0008645065,0.0006239254,0.000475003,0.001246827,0.001132124,0.0008650388,0.01101804],"category_scores_gemma":[0.0009402349,0.0009178328,0.0007390723,0.0005113946,0.0004985169,0.000637605,0.0008272783,0.001438933,0.006857079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005931663,"about_ca_system_score_gemma":0.0005841539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004597231,"about_ca_topic_score_gemma":0.0009956866,"domain_scores_codex":[0.9994229,0.00009143045,0.00006484318,0.000142061,0.0002053058,0.00007350989],"domain_scores_gemma":[0.9994817,0.0001928055,0.0001024759,0.00008908396,0.00006917345,0.00006475782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005188878,0.0000894539,0.0003946387,0.0006491363,0.00005241255,0.0003331476,0.0001572953,0.002723895,0.9445145,0.004309308,0.0118062,0.03445136],"study_design_scores_gemma":[0.00007168696,0.0001410257,0.0003641219,0.0000411112,0.00003358901,0.0003582186,0.00002008484,0.005762636,0.9166195,0.0005919565,0.07595652,0.00003962598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09874652,0.002476521,0.8132415,0.0008990836,0.0005431423,0.001458724,0.01716334,0.03967242,0.02579885],"genre_scores_gemma":[0.3079654,0.003705807,0.5920113,0.0009293729,0.0001098225,0.002740303,0.03190323,0.01441596,0.04621867],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01101804,"threshold_uncertainty_score":0.03685904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04367789731131333,"score_gpt":0.3655873714563466,"score_spread":0.3219094741450332,"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."}}