{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001427369,0.0003930598,0.0003852384,0.001158865,0.0006714084,0.0007669345,0.0004340587,0.0003376337,0.001671303],"category_scores_gemma":[0.006475489,0.0001928331,0.0002284405,0.0009597866,0.0002190572,0.0001630562,0.0007282051,0.0002900817,0.0002324875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007594708,"about_ca_system_score_gemma":0.0005646739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08467676,"about_ca_topic_score_gemma":0.09428148,"domain_scores_codex":[0.9990625,0.0004335857,0.00005288783,0.000287444,0.00009027549,0.00007334202],"domain_scores_gemma":[0.9982444,0.0007603681,0.0003709848,0.0003003907,0.0002300283,0.00009378495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001637215,0.00001659502,0.9818305,0.00004402892,0.0001510221,0.0001421256,0.0003219899,0.001760733,0.001036207,0.0000924218,0.0006540678,0.01378666],"study_design_scores_gemma":[0.00002087272,0.00005352025,0.9854506,0.00007704998,0.0001815368,0.0004867698,0.0005356112,0.009513251,0.0007986089,0.0002736814,0.002586439,0.00002210827],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912639,0.0005979727,0.003582831,0.0001535947,0.000009792233,0.00005067367,0.003172417,0.00003587182,0.00113282],"genre_scores_gemma":[0.9953184,0.0001565218,0.002375101,0.00003738784,0.000005466492,0.00002547257,0.001842959,0.000006981289,0.0002316719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08467676,"threshold_uncertainty_score":0.1683677,"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."}}