{"id":"W2028168305","doi":"10.1177/153303460500400105","title":"Geomatics for Precise 3D Breast Imaging","year":2005,"lang":"en","type":"article","venue":"Technology in Cancer Research & Treatment","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mammography; Imaging phantom; Breast cancer; Medicine; Microcalcification; Artificial intelligence; Breast imaging; Orientation (vector space); Photogrammetry; Nuclear medicine; Computer science; Computer vision; Radiology; Cancer; Mathematics; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005418448,0.000557329,0.0004094298,0.001419066,0.0005692827,0.001975883,0.001009707,0.0007862737,0.0145755],"category_scores_gemma":[0.001876917,0.0003873884,0.0007347182,0.001390498,0.001392492,0.0009401087,0.00160792,0.001177089,0.005404675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001002849,"about_ca_system_score_gemma":0.001256081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01265984,"about_ca_topic_score_gemma":0.01638568,"domain_scores_codex":[0.9995511,0.00008964686,0.0000269892,0.00005456624,0.0002510367,0.00002653871],"domain_scores_gemma":[0.9995399,0.000112091,0.00003323593,0.0001428678,0.0001491752,0.00002277414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004590796,0.00002982025,0.001088468,0.0003722418,0.00004559834,0.0003444886,0.0004291064,0.04186279,0.02210942,0.5237018,0.02881934,0.3811509],"study_design_scores_gemma":[0.00002024486,0.0000351522,0.002205557,0.0001964392,0.00002990319,0.000821354,0.0002836092,0.2584168,0.008418216,0.1554511,0.5740479,0.00007364602],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001524964,0.001207071,0.9787532,0.00065879,0.0002281784,0.00006676999,0.0004955746,0.001559189,0.01550634],"genre_scores_gemma":[0.05754985,0.002830194,0.9234024,0.0003405046,0.0001711276,0.000205876,0.0009428094,0.0004803817,0.01407694],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0145755,"threshold_uncertainty_score":0.04875994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05448889279779843,"score_gpt":0.4266597052865773,"score_spread":0.3721708124887789,"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."}}