{"id":"W4238447797","doi":"10.1093/jicru_ndp023","title":"7. Measurement of Image Quality in Mammography","year":2009,"lang":"en","type":"article","venue":"Journal of the ICRU","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mammography; Quality (philosophy); Image quality; Computer vision; Computer science; Artificial intelligence; Medical physics; Medicine; Image (mathematics); Breast cancer; Philosophy; Epistemology; Internal medicine","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":[0.002767021,0.0002762495,0.0003609424,0.001578019,0.0003005697,0.001404106,0.0007841483,0.001447001,0.003206198],"category_scores_gemma":[0.009791113,0.0002422883,0.0005443334,0.0008608539,0.0004450429,0.0008046792,0.0005854752,0.0004620304,0.001556077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004884592,"about_ca_system_score_gemma":0.0004013165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002688989,"about_ca_topic_score_gemma":0.002219182,"domain_scores_codex":[0.9966366,0.0008649969,0.0001820379,0.0001381699,0.002057092,0.0001210904],"domain_scores_gemma":[0.9948914,0.001661778,0.0004429929,0.00025284,0.002597866,0.0001531746],"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":[0.001444925,0.000254302,0.06383628,0.002196121,0.0003303446,0.0007254387,0.0004410146,0.003970628,0.2550356,0.009776841,0.01095262,0.6510359],"study_design_scores_gemma":[0.0000821107,0.002110321,0.2545601,0.0006612316,0.0005876678,0.005924236,0.0004999785,0.02588167,0.6665586,0.00677479,0.03616934,0.0001900174],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.4323068,0.0595171,0.3620801,0.007581846,0.001924514,0.0008649376,0.003436397,0.002443286,0.129845],"genre_scores_gemma":[0.8563559,0.009872752,0.1161464,0.0009751251,0.0003906997,0.000160186,0.0009290437,0.0002865003,0.01488347],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.003206198,"threshold_uncertainty_score":0.0146336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02074906042210259,"score_gpt":0.2928412313816152,"score_spread":0.2720921709595126,"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."}}