{"id":"W3093936713","doi":"10.1158/1940-6207.capr-20-0154","title":"Impact of Personalized Genetic Breast Cancer Risk Estimation With Polygenic Risk Scores on Preventive Endocrine Therapy Intention and Uptake","year":2020,"lang":"en","type":"article","venue":"Cancer Prevention Research","topic":"BRCA gene mutations in cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Institute in Oncology and Hematology; CancerCare Manitoba","funders":"","keywords":"Breast cancer; Medicine; Oncology; Internal medicine; Cancer; Endocrine system; Gynecology; Risk assessment; Hormone","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":[0.007576065,0.0004597295,0.0005614838,0.0003965548,0.000353657,0.0008583496,0.0004409021,0.0004343859,0.002086222],"category_scores_gemma":[0.02224186,0.0003182394,0.001623358,0.0005915699,0.0002553237,0.0007157823,0.0007208019,0.001024209,0.0003406011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005294371,"about_ca_system_score_gemma":0.0006965313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004517738,"about_ca_topic_score_gemma":0.005484279,"domain_scores_codex":[0.9944317,0.003920917,0.0002540816,0.0005501205,0.0006041917,0.0002389859],"domain_scores_gemma":[0.982462,0.0107769,0.003214211,0.001945312,0.0006465557,0.0009550344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004014323,0.001141174,0.9260912,0.00008483616,0.001092918,0.00003513329,0.0001928198,0.002972088,0.0002704779,0.0001805378,0.0009204518,0.06300391],"study_design_scores_gemma":[0.0003986064,0.006059316,0.9478434,0.00009816798,0.002173479,0.0001402379,0.0001974452,0.03931671,0.0009880073,0.0009091215,0.001817564,0.00005796083],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955685,0.0004849035,0.001822594,0.0004039584,0.00003707947,0.00006951658,0.0005121138,0.00005891648,0.001042535],"genre_scores_gemma":[0.9983988,0.0000724475,0.0009165448,0.00007966618,0.00001941877,0.00004296771,0.0002565133,0.0000064655,0.0002072652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007576065,"threshold_uncertainty_score":0.04006654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0389644736130916,"score_gpt":0.3970005487241406,"score_spread":0.358036075111049,"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."}}