{"id":"W3125845125","doi":"","title":"The Inevitability of Genetic Enhancement Technologies","year":2004,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Neuroethics, Human Enhancement, Biomedical Innovations","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Human enhancement; Emerging technologies; Genetic engineering; Engineering ethics; Environmental ethics; Epistemology; Political science; Computer science; Biology; Engineering; Philosophy; Artificial intelligence; Genetics","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":[0.02945709,0.000580413,0.0006397467,0.00122918,0.003563195,0.0075346,0.001477036,0.008370814,0.001856264],"category_scores_gemma":[0.03018603,0.0003210017,0.0005819679,0.0006311589,0.04711778,0.007413407,0.005312162,0.0079179,0.0005357565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002483916,"about_ca_system_score_gemma":0.003005202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004433288,"about_ca_topic_score_gemma":0.0004707207,"domain_scores_codex":[0.9750748,0.01358932,0.0008066484,0.001972417,0.007753058,0.0008036023],"domain_scores_gemma":[0.9665534,0.02497457,0.003015371,0.002366062,0.002353687,0.0007368994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000136074,0.00001506862,0.0003349219,0.00005611357,0.000005620507,0.0001649606,0.001771123,0.000244189,0.0005006488,0.9893039,0.001238438,0.006351338],"study_design_scores_gemma":[0.00001249165,0.00004485869,0.0002041571,0.0002117039,0.00001166994,0.000657165,0.001036186,0.0003392966,0.001349626,0.9212373,0.0748755,0.00002006597],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.07485306,0.02231892,0.1368879,0.3816738,0.00228161,0.0001619886,0.00006001599,0.0001740518,0.3815887],"genre_scores_gemma":[0.86913,0.01135126,0.04785962,0.0425759,0.001320153,0.0005022504,0.00002997826,0.00009233171,0.02713855],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02945709,"threshold_uncertainty_score":0.1557859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02437407390691681,"score_gpt":0.2937904853318347,"score_spread":0.2694164114249178,"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."}}