{"id":"W4310730549","doi":"10.21203/rs.3.rs-2214507/v1","title":"Contrast Enhanced Mammography in Breast Cancer Surveillance","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Ottawa Mental Health Centre","funders":"","keywords":"Mammography; Contrast (vision); Breast cancer; Cancer detection; Medicine; Medical physics; Cancer; Radiology; Computer science; Internal medicine; Artificial intelligence","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":[0.002094134,0.0003004834,0.0003717767,0.001132845,0.0001243998,0.0007213902,0.0004735992,0.0005834386,0.00152623],"category_scores_gemma":[0.008885961,0.0001765013,0.0002185338,0.0006790002,0.0002924672,0.0003761413,0.0003923931,0.0005382836,0.0003644936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000482821,"about_ca_system_score_gemma":0.0004291019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001379933,"about_ca_topic_score_gemma":0.001064301,"domain_scores_codex":[0.9985839,0.0009407026,0.00009045341,0.00009638647,0.000235885,0.00005257256],"domain_scores_gemma":[0.9962975,0.002424456,0.0004767364,0.0001301637,0.0005047576,0.000166327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001684117,0.0002659307,0.2984178,0.001506059,0.0001390808,0.00255975,0.0001827083,0.001140154,0.004722702,0.001266245,0.005815627,0.6822997],"study_design_scores_gemma":[0.0004990008,0.007352335,0.7234581,0.004799468,0.001198623,0.0705276,0.0008351926,0.01487431,0.0384267,0.003240927,0.1346371,0.00015071],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5464385,0.3892669,0.0131206,0.007243798,0.00118587,0.0002573478,0.0005172914,0.0003158707,0.04165371],"genre_scores_gemma":[0.9528949,0.03690844,0.007094277,0.0008727303,0.0005398449,0.00003760792,0.0002173836,0.00001388046,0.001420984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002094134,"threshold_uncertainty_score":0.01107496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03116362959490078,"score_gpt":0.3833888465820827,"score_spread":0.3522252169871819,"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."}}