{"id":"W2013618133","doi":"10.1118/1.3244113","title":"Poster — Wed Eve—09: Quest for a “Gold Standard” for Breast Density Evaluation","year":2009,"lang":"en","type":"article","venue":"Medical Physics","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"","keywords":"Gold standard (test); Thresholding; Breast density; Kappa; Cohen's kappa; Population; Statistics; Standard error; Mathematics; Sample (material); Artificial intelligence; Standard deviation; Computer science; Pattern recognition (psychology); Breast cancer; Medicine; Image (mathematics); Mammography; Physics","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":[0.01875143,0.0003796874,0.0005196267,0.001900223,0.000926934,0.001441602,0.0005936323,0.0007309229,0.008404993],"category_scores_gemma":[0.01428876,0.0002460578,0.0004222516,0.0004306932,0.0009253297,0.0008201369,0.001339738,0.0009983163,0.003638281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005031303,"about_ca_system_score_gemma":0.001149194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008630994,"about_ca_topic_score_gemma":0.001382091,"domain_scores_codex":[0.9964275,0.001550948,0.0002303924,0.0003232457,0.001265462,0.0002024038],"domain_scores_gemma":[0.9914877,0.002325506,0.0003788247,0.001121933,0.004173264,0.0005127774],"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":[0.00365787,0.001334521,0.1599978,0.0006734374,0.0001267886,0.001144039,0.002393502,0.001462262,0.08307181,0.007600929,0.02809301,0.710444],"study_design_scores_gemma":[0.000482005,0.01123945,0.4735683,0.001095356,0.0003734602,0.01280338,0.007001388,0.02929457,0.3259201,0.01726264,0.1205592,0.0004001751],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7344608,0.005930786,0.1807926,0.009248168,0.003429425,0.001519286,0.0009001319,0.001117327,0.06260153],"genre_scores_gemma":[0.8113382,0.00106304,0.1659742,0.0008722623,0.0007282404,0.00029054,0.0009938519,0.0003661424,0.01837353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01875143,"threshold_uncertainty_score":0.09916824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01960685277398226,"score_gpt":0.3157823844826234,"score_spread":0.2961755317086411,"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."}}