{"id":"W2998955300","doi":"10.29173/hsi233","title":"CRISPR and TALEN: Facilitating Tailored Genomes of the Future","year":2017,"lang":"en","type":"article","venue":"Health Science Inquiry","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"CRISPR; Transcription activator-like effector nuclease; Genome editing; Computational biology; Genome; Biology; Computer science; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.000381373,0.00006362399,0.00007881971,0.00002026066,0.0005521249,0.00003418156,0.0003715133,0.00003668799,0.000001882741],"category_scores_gemma":[0.00007479836,0.00004610079,0.00002456109,0.00004872097,0.0007446149,0.000006557179,0.000239339,0.00005743096,5.09748e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007332667,"about_ca_system_score_gemma":0.0001614195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002032319,"about_ca_topic_score_gemma":0.00002313944,"domain_scores_codex":[0.9993114,0.000008442701,0.0001280192,0.0002076789,0.0001366789,0.0002077667],"domain_scores_gemma":[0.9992917,0.000003686469,0.00009956996,0.0004797701,0.00004676669,0.00007856652],"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":[0.00001883568,0.00002757691,0.07106415,0.0003041698,0.00001039962,7.001262e-7,0.004507389,0.0003147756,0.7838933,0.0003753807,0.001541954,0.1379414],"study_design_scores_gemma":[0.000356617,0.0002479646,0.8266479,0.00005411753,0.000004143682,0.0000224385,0.004661487,0.0006049675,0.1509913,0.0001128389,0.01609042,0.0002058181],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937874,0.003436058,0.000883827,0.001010897,0.000628487,0.0001121117,0.000004084762,0.000003320918,0.0001337889],"genre_scores_gemma":[0.9981456,0.0003665027,0.001025541,0.0001655551,0.0002316022,0.000003581254,8.808566e-7,0.000003845523,0.00005685736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7555837,"threshold_uncertainty_score":0.4246554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02631264069838381,"score_gpt":0.3830855437457636,"score_spread":0.3567729030473799,"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."}}