{"id":"W4408972975","doi":"10.1093/aje/kwaf067","title":"Interactions between genetic and epidemiological factors influencing mammographic density","year":2025,"lang":"en","type":"article","venue":"American Journal of Epidemiology","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of British Columbia; BC Cancer Agency","funders":"National Cancer Institute; Medical Research Council; Ministerio de Sanidad, Servicios Sociales e Igualdad; Department of Health and Social Care; National Institute for Health and Care Research; Genome Canada; NIHR Cambridge Biomedical Research Centre; European Commission; Breast Cancer Research Foundation; Servicio Gallego de Salud; Instituto de Salud Carlos III; Amgen; Cancer Council Western Australia; Pfizer; Fondation du cancer du sein du Québec; National Institutes of Health; Ovarian Cancer Research Fund; National Health and Medical Research Council; Cancer Research UK; Xunta de Galicia; Government of Canada; Canadian Institutes of Health Research; Pharmavite","keywords":"Epidemiology; MAMMOGRAPHIC DENSITY; Medicine; Genetic epidemiology; Environmental health; Mammography; Genetics; Biology; Breast cancer; Internal medicine; Cancer","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001658422,0.00047276,0.0005241768,0.001232608,0.000450924,0.0008488727,0.0004341113,0.0004591687,0.001882784],"category_scores_gemma":[0.007361768,0.0003429016,0.0009029314,0.001355813,0.0005505885,0.0002883735,0.0008350565,0.0005903657,0.00011434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003189319,"about_ca_system_score_gemma":0.0004579812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006871853,"about_ca_topic_score_gemma":0.009020505,"domain_scores_codex":[0.9959463,0.002339785,0.0002209523,0.000669305,0.0004455024,0.0003781983],"domain_scores_gemma":[0.9951474,0.003090536,0.0007435549,0.0004713885,0.0002478049,0.0002992595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002933964,0.00004330177,0.9912028,0.00002047843,0.0006616499,0.0001963572,0.00008938976,0.0002821854,0.002672623,0.000205214,0.0000874941,0.004245046],"study_design_scores_gemma":[0.00000716466,0.00005560181,0.9979345,0.000003769287,0.0001769555,0.0001560079,0.00006008665,0.0009525584,0.0002786695,0.0002224009,0.0001468425,0.000005532441],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945824,0.0006925233,0.002832987,0.0002057633,0.00001678469,0.00001998584,0.000529708,0.00003650443,0.00108336],"genre_scores_gemma":[0.9986762,0.00009421116,0.0008238367,0.00002919661,0.00000885767,0.00001158243,0.0001594895,0.000007335077,0.000189257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006871853,"threshold_uncertainty_score":0.01366371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04137325028270535,"score_gpt":0.3408884061418635,"score_spread":0.2995151558591582,"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."}}