{"id":"W3161687379","doi":"10.1093/jncics/pkab015","title":"Relation of Quantitative Histologic and Radiologic Breast Tissue Composition Metrics With Invasive Breast Cancer Risk","year":2021,"lang":"en","type":"article","venue":"JNCI Cancer Spectrum","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Cancer Institute; Breast Cancer Research Foundation; Division of Cancer Epidemiology and Genetics, National Cancer Institute; U.S. Department of Health and Human Services","keywords":"Medicine; Breast cancer; Breast tissue; Radiology; Pathology; Oncology; Internal medicine; Cancer","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":[0.00009745852,0.0001831463,0.0004269203,0.0002395115,0.00008775913,0.00002444805,0.00005136355,0.00007422786,0.0001411029],"category_scores_gemma":[0.00002799304,0.0001423798,0.00007093159,0.001020645,0.0002393568,0.000236787,0.00002784275,0.0002238458,0.000002278496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00022629,"about_ca_system_score_gemma":0.00026162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001457733,"about_ca_topic_score_gemma":0.0003903769,"domain_scores_codex":[0.9988604,0.00006720297,0.0002441754,0.0003546268,0.0002410695,0.000232533],"domain_scores_gemma":[0.9990935,0.0001257973,0.0002764005,0.0001756183,0.0002168885,0.0001118073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009503171,0.0002218411,0.9611617,0.0002275892,0.0004305643,0.0002232832,0.0004355685,0.000153122,0.007364942,0.002303463,0.0002769898,0.02625056],"study_design_scores_gemma":[0.001318613,0.0004276464,0.9854892,0.0003880223,0.0004139346,0.002447394,0.0002974151,0.0001581047,0.008079383,0.000703437,0.00008424879,0.0001926213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982976,0.009247527,0.001055336,0.00377751,0.0001985917,0.0002654878,0.0004589199,0.00005205907,0.001968558],"genre_scores_gemma":[0.9957084,0.002685114,0.001127723,0.0001809876,0.00009731988,0.00002825286,0.00005731057,0.00001770181,0.00009718557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02605794,"threshold_uncertainty_score":0.5806079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01342258071323182,"score_gpt":0.2726252269407217,"score_spread":0.2592026462274899,"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."}}