{"id":"W4285225387","doi":"10.7202/1089801ar","title":"The Better I Can Be: In Defence of Human Enhancement for a New Genetic Equality","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Bioethics","topic":"Neuroethics, Human Enhancement, Biomedical Innovations","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Argument (complex analysis); Inequality; Dimension (graph theory); Value (mathematics); Human enhancement; Environmental ethics; Human genetic variation; Sociology; Epistemology; Law and economics; Positive economics; Computer science; Genetics; Biology; Human genome; Mathematics; Economics; Philosophy; Genome; Gene; Pure mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001802813,0.000116993,0.0001971708,0.0003106986,0.0007898786,0.00005447229,0.0008713136,0.0000666029,0.0001862863],"category_scores_gemma":[0.001845062,0.0001045492,0.00008855423,0.0006339536,0.001129603,0.00005470215,0.00007080937,0.001088726,7.218918e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003505393,"about_ca_system_score_gemma":0.003094149,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005363677,"about_ca_topic_score_gemma":0.0765226,"domain_scores_codex":[0.997539,0.0003418021,0.0008739164,0.0002120492,0.0006068501,0.0004263907],"domain_scores_gemma":[0.997783,0.0007968901,0.0006033474,0.0002991046,0.0001936795,0.0003239633],"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":[0.00009374195,0.0002113625,0.002578774,0.0001536084,0.00004793268,0.000178359,0.0129884,0.0002271109,0.7516608,0.1978261,0.02193433,0.01209945],"study_design_scores_gemma":[0.002515264,0.002926313,0.002900839,0.0001710763,0.00006379382,0.0001072883,0.00248913,0.000175252,0.668105,0.1500115,0.1699022,0.0006323254],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8833298,0.0002250656,0.003320732,0.1105222,0.001482539,0.0006063106,0.0002087937,0.000006017679,0.0002985726],"genre_scores_gemma":[0.9884582,0.00003146004,0.0004836586,0.01046083,0.0001177843,0.00002086641,0.000002076649,0.00001569873,0.000409418],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1479679,"threshold_uncertainty_score":0.9403285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2130907798800652,"score_gpt":0.3827030713328495,"score_spread":0.1696122914527843,"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."}}