{"id":"W2581771809","doi":"10.1038/s41536-017-0007-2","title":"Human gene editing: revisiting Canadian policy","year":2017,"lang":"en","type":"editorial","venue":"npj Regenerative Medicine","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ottawa Hospital; NeuroDevNet; University of British Columbia; McGill University; University of Ottawa; Institute of Health Economics; McGill Genome Centre; Université de Montréal; University of Alberta; McGill University Health Centre","funders":"","keywords":"Genome editing; Gene; Political science; Biology; Genetics; CRISPR","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005329004,0.0005547928,0.0006235983,0.0002801939,0.000597525,0.00006420456,0.000639851,0.0009309266,0.00007511659],"category_scores_gemma":[0.002855728,0.0005071163,0.0001361787,0.00009083816,0.0002619234,0.000003669078,0.0001492147,0.0006273501,0.00001381838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001651527,"about_ca_system_score_gemma":0.001114038,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02413591,"about_ca_topic_score_gemma":0.03278113,"domain_scores_codex":[0.9974995,0.0000824413,0.0004503462,0.0008034439,0.0004973988,0.0006668839],"domain_scores_gemma":[0.9976548,0.00002867177,0.0003064697,0.001056728,0.0004707471,0.0004825881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003732753,0.000003741859,0.00001315001,0.00006214895,0.00009545508,0.00004160092,0.00008409846,0.00003749631,0.1164659,0.00005740096,0.8817336,0.001401651],"study_design_scores_gemma":[0.0006526119,0.0002717634,0.00003752844,0.0002978577,0.00007226277,0.00001369078,0.0000381318,0.00001303386,0.04544079,0.00002065711,0.9527008,0.0004408782],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.001785313,0.01725662,0.001772809,0.003929818,0.9304889,0.0007226554,0.0006708996,0.00006279894,0.04331012],"genre_scores_gemma":[0.01894111,0.0005494311,0.0002761219,0.0001581128,0.9560429,0.00004172386,0.004496853,0.0001170519,0.01937663],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.07102513,"threshold_uncertainty_score":0.999738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01258558102727118,"score_gpt":0.3556121449024052,"score_spread":0.343026563875134,"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."}}