{"id":"W4300841564","doi":"","title":"SOUND-SPEED AND ATTENUATION IMAGING OF BREAST TISSUE USING WAVEFORM TOMOGRAPHY OF TRANSMISSION ULTRASOUND DATA","year":2024,"lang":"en","type":"paratext","venue":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","topic":"Infrared Thermography in Medicine","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Los Alamos National Laboratory; Natural Sciences and Engineering Research Council of Canada; National Nuclear Security Administration; U.S. Department of Energy","keywords":"Attenuation; Acoustics; Ultrasound; Waveform; Tomography; Speed of sound; Iterative reconstruction; Transmission (telecommunications); Breast imaging; Acoustic attenuation; Ultrasound imaging; Ultrasonic imaging; Computer science; Physics; Radiology; Optics; Medicine; Mammography; Breast cancer; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0005317978,0.0004003444,0.0001551702,0.0009872231,0.00006878124,0.0004499648,0.0003791584,0.0003327368,0.003046573],"category_scores_gemma":[0.002659505,0.000198874,0.0001812094,0.000757773,0.0002239323,0.0005361443,0.0002931858,0.0002347593,0.0003288008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000168434,"about_ca_system_score_gemma":0.0002724887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009530312,"about_ca_topic_score_gemma":0.0007256095,"domain_scores_codex":[0.9998202,0.00003852191,0.00001250677,0.00001839353,0.0000950756,0.00001527836],"domain_scores_gemma":[0.9993967,0.0002928749,0.00007307335,0.00005547773,0.0001609076,0.00002101869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009406485,0.0001190785,0.006638321,0.000540622,0.00005641507,0.000530586,0.0003362797,0.07269982,0.6998823,0.002828562,0.0005273592,0.2149001],"study_design_scores_gemma":[0.00005714039,0.0007457379,0.02006876,0.00006562997,0.0001066525,0.003980956,0.0002011259,0.6450991,0.3241864,0.001080918,0.004319453,0.00008817911],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6858223,0.0004777997,0.3090686,0.0001448058,0.00001824119,0.00008038669,0.0002926301,0.001079085,0.003016257],"genre_scores_gemma":[0.8252504,0.0005715064,0.1714937,0.00003377338,0.00001658456,0.00005728621,0.00060611,0.0002407565,0.001729824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003046573,"threshold_uncertainty_score":0.0101918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01834956522411627,"score_gpt":0.2773387317737167,"score_spread":0.2589891665496004,"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."}}