{"id":"W7108733851","doi":"10.5376/cmb.2025.15.0010","title":"Computational Prediction of Off-Target Effects in CRISPR Systems CRISPR","year":2025,"lang":"","type":"article","venue":"Computational Molecular Biology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"CRISPR; Process (computing); Computational model; Field (mathematics); Key (lock); Genome editing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008876937,0.000715839,0.00110141,0.0004788691,0.0004469474,0.0010951,0.001001907,0.00112187,0.001628931],"category_scores_gemma":[0.002894881,0.0004405737,0.0008306077,0.0003994885,0.0005929826,0.0006287463,0.0006807814,0.001043603,0.0002016741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008271703,"about_ca_system_score_gemma":0.001441706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009458525,"about_ca_topic_score_gemma":0.005534726,"domain_scores_codex":[0.9997119,0.00009596646,0.00001887244,0.00006854654,0.00005803084,0.00004665658],"domain_scores_gemma":[0.9983212,0.001324618,0.00009136679,0.00006475255,0.0001377682,0.00006016998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002548707,0.00001709297,0.0009761674,0.00004188109,0.00001544691,0.00004284639,0.000009264856,0.9928208,0.0004143303,0.002070155,0.0002050978,0.003361337],"study_design_scores_gemma":[0.00000327927,0.00000706393,0.00008421709,0.000002237535,0.000003950774,0.000003671746,0.000002678211,0.9987761,0.0001774393,0.0008536285,0.00008357151,0.00000210382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4727231,0.001723723,0.5089176,0.00102942,0.0001706011,0.0001181802,0.0008852857,0.001373564,0.01305868],"genre_scores_gemma":[0.9394503,0.0005823931,0.0563432,0.0002157149,0.00003260078,0.0001928362,0.0007642058,0.0001427728,0.002276011],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009458525,"threshold_uncertainty_score":0.01880693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004256948384104758,"score_gpt":0.3087525044499577,"score_spread":0.3044955560658529,"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."}}