{"id":"W2805282888","doi":"10.1016/j.tibtech.2018.04.008","title":"Building Capacity for a Global Genome Editing Observatory: Institutional Design","year":2018,"lang":"en","type":"article","venue":"Trends in biotechnology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"National Institute of General Medical Sciences; World Health Organization","keywords":"Observatory; Genome editing; Key (lock); Reflection (computer programming); Genome; Capacity building; Computer science; Biology; Political science; Gene; Genetics; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001708253,0.0001332206,0.0001262301,0.0001024492,0.00007963465,0.000008225574,0.0002170272,0.0003824803,0.00000909784],"category_scores_gemma":[0.0000977683,0.0001445656,0.00005066966,0.0002634755,0.0002280449,0.000002758806,0.00009835011,0.00008900965,0.000002457628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004758042,"about_ca_system_score_gemma":0.00002932154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001179931,"about_ca_topic_score_gemma":0.00008888615,"domain_scores_codex":[0.9991083,0.00001401145,0.0001657065,0.0003353398,0.00005349362,0.0003231401],"domain_scores_gemma":[0.9996525,0.00000650523,0.00003725705,0.0002316407,0.00003694303,0.00003512182],"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":[0.0000522681,0.00003897952,0.0008196752,0.00001241417,0.00003412539,0.000002886718,0.00001503229,0.001080529,0.9380788,0.01377376,0.0003856053,0.04570592],"study_design_scores_gemma":[0.00110788,0.000664053,0.007861644,0.00001789575,0.0000156538,0.0000704026,0.00001836866,0.002342296,0.8090911,0.002106363,0.1763356,0.0003687975],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4198681,0.0002470368,0.5789299,0.0003109882,0.0002862545,0.00008373453,0.0000277182,0.00004770705,0.0001986053],"genre_scores_gemma":[0.845468,0.00001342725,0.1538844,0.00008002642,0.0004461173,0.00003515816,0.00002810382,0.00001042725,0.00003432855],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4256,"threshold_uncertainty_score":0.5895216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03572064149874072,"score_gpt":0.3246312084591317,"score_spread":0.288910566960391,"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."}}