{"id":"W2891195522","doi":"10.1159/000492663","title":"Ethical, Legal, and Regulatory Issues for the Implementation of Omics-Based Risk Prediction of Women’s Cancer: Points to Consider","year":2018,"lang":"en","type":"article","venue":"Public Health Genomics","topic":"BRCA gene mutations in cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Quebec Population Health Research Network; McGill University; McGill Genome Centre","funders":"European Commission","keywords":"Omics; Ethical issues; Psychological intervention; Breast cancer; Medicine; Cancer; Risk analysis (engineering); Bioinformatics; Biology; Engineering ethics; Internal medicine; Nursing; Engineering","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3490287,0.001214389,0.001613288,0.003278009,0.01300512,0.02136793,0.005978941,0.02519653,0.00328111],"category_scores_gemma":[0.3800422,0.001098207,0.002320046,0.002792216,0.04134822,0.01965047,0.01290509,0.03042711,0.0007539956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01678401,"about_ca_system_score_gemma":0.1056057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01227549,"about_ca_topic_score_gemma":0.01185395,"domain_scores_codex":[0.6678093,0.2359225,0.02454158,0.008518912,0.05061914,0.01258854],"domain_scores_gemma":[0.4372219,0.4265228,0.02961057,0.0269773,0.06356106,0.01610641],"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":[0.0001140732,0.0004371428,0.01057847,0.001533505,0.0001739877,0.002212405,0.03579545,0.003788584,0.001704669,0.6941603,0.09995854,0.1495428],"study_design_scores_gemma":[0.0001072789,0.0002784403,0.008469794,0.01191676,0.0001922381,0.001709097,0.04277936,0.003950772,0.002362824,0.6306947,0.2970229,0.0005158585],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01243226,0.007286995,0.06936575,0.8834399,0.003057441,0.0008303185,0.0001237723,0.0001886599,0.02327494],"genre_scores_gemma":[0.4027717,0.008527528,0.3243752,0.2511078,0.003433656,0.003054264,0.0003092603,0.0002844443,0.00613615],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3490287,"threshold_uncertainty_score":0.8027636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03407551252214344,"score_gpt":0.3747844998921954,"score_spread":0.340708987370052,"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."}}