{"id":"W2139292200","doi":"10.1118/1.3457710","title":"Tissue typing using ultrasound RF time series: Experiments with animal tissue samples","year":2010,"lang":"en","type":"article","venue":"Medical Physics","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of British Columbia; University of British Columbia Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Health Canada; Cummings Foundation","keywords":"Radio frequency; Ultrasound; Frame rate; Biomedical engineering; RF power amplifier; Materials science; Computer science; Artificial intelligence; Acoustics; Medicine; Bandwidth (computing); Physics; Telecommunications","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":[],"consensus_categories":[],"category_scores_codex":[0.000167045,0.0002462662,0.0003654002,0.00005051213,0.0001748919,0.00004834026,0.0001508506,0.0001381492,0.0007041371],"category_scores_gemma":[0.000227917,0.0001909645,0.00005820634,0.0003081608,0.0004852577,0.0001902638,0.0000364423,0.0005949605,0.0001448816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002431407,"about_ca_system_score_gemma":0.0001994507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001305674,"about_ca_topic_score_gemma":0.000007126408,"domain_scores_codex":[0.9983549,0.00002103794,0.0002215071,0.0003514101,0.0006237506,0.0004273678],"domain_scores_gemma":[0.9989321,0.0001396381,0.00006970395,0.0003532635,0.00009072619,0.0004146083],"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":[0.0001780993,0.0003450326,0.01146939,0.00006830261,0.0001430026,0.00003006504,0.0009413674,0.000001658987,0.9730289,0.0001601383,0.0006733252,0.01296075],"study_design_scores_gemma":[0.004002321,0.002193579,0.01134688,0.0009093714,0.0005844348,0.003173027,0.0005584945,0.0002270975,0.782627,0.000914685,0.1922285,0.001234636],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9804403,0.00009933968,0.01650252,0.000363914,0.0002827822,0.0002125969,0.00001100816,0.0001800345,0.001907531],"genre_scores_gemma":[0.9803457,0.00001105969,0.01718758,0.0005793484,0.001355418,0.00001028311,0.00006409355,0.00006390556,0.000382568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1915551,"threshold_uncertainty_score":0.7787308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01603522003107958,"score_gpt":0.2924186230965515,"score_spread":0.2763834030654719,"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."}}