{"id":"W4392499120","doi":"10.3390/cancers16051076","title":"The Convergence of Radiology and Genomics: Advancing Breast Cancer Diagnosis with Radiogenomics","year":2024,"lang":"en","type":"article","venue":"Cancers","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network","funders":"Medical Research Council; South African Medical Research Council; National Research Foundation","keywords":"Radiogenomics; Medicine; Precision medicine; Context (archaeology); Disease; Intensive care medicine; Breast cancer; Bioinformatics; Cancer; Pathology; Internal medicine; Radiomics; Biology; Radiology","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":[0.003462326,0.0006924622,0.001332448,0.001993502,0.0004440094,0.002881822,0.0009707669,0.002150685,0.002374908],"category_scores_gemma":[0.005058147,0.0003388575,0.0009430898,0.00198444,0.002392089,0.003011374,0.001549178,0.003203633,0.001015797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001507432,"about_ca_system_score_gemma":0.002532625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002018705,"about_ca_topic_score_gemma":0.002421675,"domain_scores_codex":[0.9985549,0.0006554189,0.0001012581,0.0001999994,0.0003903788,0.00009803528],"domain_scores_gemma":[0.9957706,0.003099747,0.0002183511,0.0001373703,0.0006267875,0.0001471294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001065224,0.00006817237,0.003040441,0.0160375,0.0003289252,0.0007679222,0.001157974,0.002053877,0.009073926,0.07857993,0.04195414,0.8468307],"study_design_scores_gemma":[0.00001631709,0.0001318775,0.003370696,0.006194144,0.0001824277,0.002116835,0.0007688473,0.001364146,0.002868727,0.06312841,0.9197543,0.0001033313],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001510121,0.96246,0.01343233,0.01611327,0.001184042,0.00002280729,0.0001312882,0.000106812,0.005039304],"genre_scores_gemma":[0.01421301,0.9681843,0.01022868,0.004515973,0.001660326,0.00004064347,0.000132123,0.00003397518,0.0009909832],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003462326,"threshold_uncertainty_score":0.01831079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005569263858952556,"score_gpt":0.2659851280676395,"score_spread":0.2604158642086869,"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."}}