{"id":"W1536526355","doi":"10.1089/omi.2007.0042","title":"Integrating Anticipated Nutrigenomics Bioscience Applications with Ethical Aspects","year":2008,"lang":"en","type":"article","venue":"OMICS A Journal of Integrative Biology","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"Nutrigenomics; Bioethics; Engineering ethics; Medicine; Context (archaeology); Engineering; Biology; Genetics","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":[0.0002488348,0.0001987029,0.0002867169,0.0001266062,0.0001807939,0.00001731624,0.0003338973,0.0002640055,0.000009860437],"category_scores_gemma":[0.0002806831,0.0001310394,0.0001276674,0.0001920116,0.0007051987,0.000005909594,0.00005014213,0.0004016487,0.000003248744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004216109,"about_ca_system_score_gemma":0.0007086128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009692079,"about_ca_topic_score_gemma":0.00003964015,"domain_scores_codex":[0.9988326,0.0001376305,0.0004209257,0.0002683384,0.0001009223,0.0002395568],"domain_scores_gemma":[0.9983632,0.00005474489,0.0003789685,0.0002079429,0.0008196256,0.000175522],"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":[0.0007598158,0.0003551853,0.02051402,0.00001224759,0.0001499456,0.00003037743,0.0003694739,0.00002815199,0.9520913,0.02389005,0.0006955147,0.001103939],"study_design_scores_gemma":[0.00505278,0.008916246,0.008619779,0.000153199,0.0001644347,0.003665776,0.002718879,0.0002484747,0.8732549,0.01130375,0.08483256,0.001069255],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8936304,0.001276704,0.1032306,0.0003743912,0.0001211326,0.0002045388,0.00005931352,0.000006448457,0.001096504],"genre_scores_gemma":[0.984809,0.001719308,0.01237196,0.0006060156,0.0003530531,0.00001186773,0.00005770618,0.00001643866,0.00005457943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09117868,"threshold_uncertainty_score":0.534363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01524385118833278,"score_gpt":0.2880672243781595,"score_spread":0.2728233731898267,"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."}}