{"id":"W2088047356","doi":"10.1002/cncr.20971","title":"Screening women at high risk for breast cancer with mammography and magnetic resonance imaging","year":2005,"lang":"en","type":"article","venue":"Cancer","topic":"BRCA gene mutations in cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":400,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"National Cancer Institute","keywords":"Medicine; Mammography; Breast cancer; Magnetic resonance imaging; Asymptomatic; Breast MRI; Cancer; Biopsy; Radiology; Breast cancer screening; Confidence interval; Occult; Overdiagnosis; Internal medicine; Pathology","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":[0.00008947757,0.0001666733,0.0001260889,0.00004462623,0.000177169,0.00002778064,0.0001139201,0.00005847635,0.0001818949],"category_scores_gemma":[0.000005621707,0.0001523256,0.0000367244,0.0001184262,0.000157013,0.000008587906,0.00006933731,0.00006596294,0.0000010373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001703793,"about_ca_system_score_gemma":0.000110494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001856463,"about_ca_topic_score_gemma":0.0009095476,"domain_scores_codex":[0.9989547,0.00001881204,0.0001278109,0.0004491049,0.00009970835,0.0003498859],"domain_scores_gemma":[0.999467,0.00001145515,0.00008123382,0.0002453917,0.0001022179,0.0000926819],"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":[0.0006273189,0.00001574848,0.2310577,0.00003013932,0.00006338806,0.000001027467,0.0002294544,0.001321281,0.01561282,0.00001552882,0.007162754,0.7438628],"study_design_scores_gemma":[0.003137172,0.000172028,0.4022941,0.00008713208,0.00009662624,0.00004441155,0.0001620708,0.0008284943,0.02442507,0.00005701364,0.5681184,0.000577461],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.944305,0.05166685,0.001410524,0.00112989,0.0001154352,0.0002958176,0.0009610025,0.00001921772,0.00009625983],"genre_scores_gemma":[0.9853896,0.003608565,0.006723052,0.0009200262,0.0007565668,0.001110721,0.00002375744,0.00005380813,0.001413936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7432854,"threshold_uncertainty_score":0.6211656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00452599221350232,"score_gpt":0.2353709997363298,"score_spread":0.2308450075228275,"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."}}