{"id":"W4323519613","doi":"10.2139/ssrn.4375726","title":"Somatic Genome Editing Governance Approaches and Regulatory Capacity in Different Countries","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Cancer Research","funders":"","keywords":"Corporate governance; Genome; Somatic cell; Genome editing; Biology; Computational biology; Genetics; Political science; Business; Gene","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":[0.003206603,0.0001896478,0.0001959056,0.001314373,0.0006629609,0.002896989,0.0005173923,0.0004898518,0.002847409],"category_scores_gemma":[0.003824213,0.0001474031,0.0002411318,0.002036443,0.001578842,0.0009921243,0.001152989,0.0009052581,0.0002962405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002521688,"about_ca_system_score_gemma":0.002987852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004152637,"about_ca_topic_score_gemma":0.004306921,"domain_scores_codex":[0.9981651,0.0003846333,0.0001350708,0.0005353183,0.0003329975,0.0004468343],"domain_scores_gemma":[0.996425,0.001038805,0.0007583831,0.0005815041,0.0006856336,0.0005106886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0007790466,0.0002284824,0.04541846,0.0005512083,0.0002603866,0.0009511508,0.004184419,0.006933205,0.03704461,0.5653076,0.008104246,0.3302371],"study_design_scores_gemma":[0.0002026829,0.001024968,0.3787313,0.0008825886,0.0004041679,0.001749958,0.00857423,0.005510211,0.06301528,0.05676333,0.4828351,0.0003061569],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7799916,0.007690939,0.02604306,0.005309446,0.0003154513,0.0001321733,0.0009553489,0.0004484361,0.1791134],"genre_scores_gemma":[0.9804314,0.001658524,0.005414724,0.0004071917,0.00002403965,0.00004423121,0.0004101498,0.00005908616,0.01155067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004152637,"threshold_uncertainty_score":0.01829624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0116427683548017,"score_gpt":0.2262077704763679,"score_spread":0.2145650021215663,"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."}}