{"id":"W4413494925","doi":"10.1038/s41597-025-05866-0","title":"Full Field Digital Mammography Dataset from a Population Screening Program","year":2025,"lang":"en","type":"article","venue":"Scientific Data","topic":"AI in cancer detection","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. John’s Health Sciences Centre; Newfoundland and Labrador Centre for Applied Health Research; Memorial University of Newfoundland","funders":"Memorial University of Newfoundland","keywords":"Mammography; Field (mathematics); Population; Digital mammography; Mammography screening; Data science; Computer science; Medical physics; Medicine; Environmental health; Mathematics; Breast cancer; Internal medicine; Cancer","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0006736339,0.001400602,0.001075907,0.002720654,0.0007982191,0.001077002,0.002476986,0.001658065,0.009802539],"category_scores_gemma":[0.003214325,0.0003524994,0.001077608,0.003868364,0.0004450298,0.0003977334,0.001026658,0.001047942,0.01041016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002419414,"about_ca_system_score_gemma":0.003410431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1993557,"about_ca_topic_score_gemma":0.3209101,"domain_scores_codex":[0.9991418,0.000107644,0.00007719207,0.0002204108,0.0003062191,0.0001467376],"domain_scores_gemma":[0.9985805,0.0002771758,0.00009669125,0.0002731973,0.0006077696,0.0001647353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006535833,0.0005127129,0.02468203,0.001440662,0.0002838088,0.0005381226,0.00009261786,0.003500856,0.001500058,0.0005404885,0.9274887,0.03876635],"study_design_scores_gemma":[0.0007028237,0.0002767058,0.1834606,0.0006977408,0.0003615522,0.001791802,0.0005145867,0.01700943,0.00411865,0.002364022,0.7885066,0.0001954811],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01018799,0.0007370886,0.0005523299,0.000393822,0.00006408681,0.0001266761,0.9846501,0.0009553557,0.002332543],"genre_scores_gemma":[0.0087821,0.0002101959,0.001353275,0.0001139915,0.00001918108,0.00008744587,0.9884567,0.00002708908,0.0009500465],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1993557,"threshold_uncertainty_score":0.3963906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03314364068906861,"score_gpt":0.3164268363211404,"score_spread":0.2832831956320718,"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."}}