{"id":"W4405096693","doi":"10.1007/s10549-024-07557-7","title":"Inference of genetic ancestry from a multi-gene cancer panel in Colombian women with cancer","year":2024,"lang":"en","type":"article","venue":"Breast Cancer Research and Treatment","topic":"Race, Genetics, and Society","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; McGill University","funders":"National Cancer Institute; Instituto Nacional de Cancerología; Georgia Institute of Technology","keywords":"Genetic genealogy; Ancestry-informative marker; Cancer; Population; 1000 Genomes Project; Cohort; Inference; Breast cancer; Genetics; Health equity; Genetic testing; Biology; Demography; Medicine; Gene; Allele frequency; Genotype; Internal medicine; Public health; Single-nucleotide polymorphism; Environmental health; Pathology; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000104191,0.0001952743,0.0002330176,0.00006183003,0.00008077815,0.00005119824,0.0001317383,0.0001233364,0.0001088049],"category_scores_gemma":[0.000004872465,0.000148619,0.00003563962,0.0002168397,0.0003328323,0.000006582891,0.00007830877,0.0001285668,0.000001735362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003111693,"about_ca_system_score_gemma":0.001010841,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03115009,"about_ca_topic_score_gemma":0.02583887,"domain_scores_codex":[0.9984182,0.00007068889,0.0001845737,0.0005864371,0.0002403692,0.0004997076],"domain_scores_gemma":[0.9993388,0.00002879196,0.00003511026,0.0002680962,0.0001359914,0.0001931856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001348539,0.0006073747,0.6553536,0.0001708504,0.0009083444,0.00008498754,0.003469357,0.000653605,0.1702366,0.000009090017,0.0002206744,0.166937],"study_design_scores_gemma":[0.002882237,0.001286926,0.9313312,0.0003453111,0.00004287742,0.00001210503,0.001035162,0.0004950715,0.05904599,0.00007906317,0.003116603,0.0003275022],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9616112,0.03627525,0.0000269067,0.0003294471,0.00007407925,0.0003511955,0.001289448,0.0000080498,0.00003446542],"genre_scores_gemma":[0.9432899,0.05426486,0.0002598617,0.00002951233,0.0001992506,0.001203655,0.00003638172,0.00002682154,0.0006898139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2759776,"threshold_uncertainty_score":0.991937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06512567454030706,"score_gpt":0.370763756519742,"score_spread":0.3056380819794349,"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."}}