{"id":"W2793007601","doi":"10.1007/s10549-018-4737-7","title":"Mammographic non-dense area and breast cancer risk in postmenopausal women: a causal inference approach in a case–control study","year":2018,"lang":"en","type":"article","venue":"Breast Cancer Research and Treatment","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Centre for Applied Research in Cancer Control; Queen's University; Spinal Cord Injury BC; University of British Columbia","funders":"University of British Columbia Graduate School; Canadian Institutes of Health Research; Canadian Cancer Society","keywords":"Quartile; Breast cancer; Medicine; Confounding; Akaike information criterion; Odds ratio; Statistics; Logistic regression; Case-control study; Population; Cancer; Gynecology; Demography; Internal medicine; Mathematics; Confidence interval; Environmental health","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006854789,0.000392613,0.0006231858,0.001164261,0.0002308358,0.0001641849,0.00009309886,0.00008783805,0.00008764648],"category_scores_gemma":[0.00001476899,0.000290272,0.00005069508,0.001446643,0.0006641758,0.0002773622,0.00009382886,0.0004305483,0.000003049838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006370699,"about_ca_system_score_gemma":0.0004385119,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04691058,"about_ca_topic_score_gemma":0.01618155,"domain_scores_codex":[0.9969004,0.000227394,0.0003537916,0.0008654774,0.0005167408,0.001136157],"domain_scores_gemma":[0.9985331,0.0001554472,0.00006928982,0.0003673267,0.0002487408,0.0006261122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004937153,0.003367466,0.8337682,0.00005369114,0.0004588698,0.003559582,0.002812086,0.000002407846,0.00006009779,0.00001224889,0.0000122546,0.1509559],"study_design_scores_gemma":[0.013095,0.004339831,0.9702734,0.0002418313,0.0001087819,0.007390062,0.003731457,0.0004415689,0.000007279607,0.0001107053,0.00001332468,0.0002467853],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994248,0.001244826,0.000006261639,0.0006971254,0.00003616494,0.002015681,0.001285911,0.00002953545,0.0004364332],"genre_scores_gemma":[0.9964826,0.0009769724,0.00002889477,0.00005792861,0.0001756566,0.002151563,0.00000785626,0.00003587941,0.00008265268],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1507091,"threshold_uncertainty_score":0.9999549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02825839175775973,"score_gpt":0.3395388196869492,"score_spread":0.3112804279291894,"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."}}