{"id":"W3182330586","doi":"10.1111/bioe.12913","title":"From goodness to good looks: Changing images of human germline genetic modification","year":2021,"lang":"en","type":"article","venue":"Bioethics","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill Genome Centre","funders":"Canadian Institutes of Health Research","keywords":"Context (archaeology); Trait; Identity (music); Germline; Sociology; Bioethics; Psychology; Aesthetics; Social psychology; Political science; Biology; Law; Genetics; Computer science; Art","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001144138,0.0001125002,0.0001247107,0.00004718341,0.00004884585,0.000016117,0.0001336578,0.0001575639,0.00001778155],"category_scores_gemma":[0.00007174689,0.0001259997,0.00006155748,0.0001356899,0.00005248877,0.000001379793,0.0001249446,0.00008393809,0.000006057469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007223224,"about_ca_system_score_gemma":0.00004911387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007238532,"about_ca_topic_score_gemma":0.00004980601,"domain_scores_codex":[0.9991888,0.00003076604,0.0001981523,0.0002881664,0.0001201124,0.000173947],"domain_scores_gemma":[0.9993134,0.00001287288,0.00004645814,0.000406726,0.0001526038,0.00006794269],"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":[0.000005087895,0.00003390653,0.0005217684,0.00003224263,0.00002665102,0.000002687119,0.0002803916,0.0004649469,0.9966956,0.0001504394,0.0001040873,0.001682124],"study_design_scores_gemma":[0.0001838573,0.00006922611,0.004898021,0.00002950684,0.00002270001,0.000002845412,0.0004184585,0.0001203385,0.992384,0.0001105091,0.001607272,0.0001532716],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9127713,0.002492983,0.08378116,0.000329256,0.0001846256,0.00009224538,0.00007544309,0.00001537853,0.0002576075],"genre_scores_gemma":[0.9911936,0.0001364145,0.00749305,0.0001237086,0.0003812328,0.00001105193,0.0002227732,0.00002263466,0.0004155616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07842227,"threshold_uncertainty_score":0.5138118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03637848518404686,"score_gpt":0.375443505657528,"score_spread":0.3390650204734811,"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."}}