{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001699896,0.0004480972,0.0004726401,0.0006504878,0.0002478928,0.0003186757,0.000465986,0.0007319688,0.0007958171],"category_scores_gemma":[0.003972943,0.0002226907,0.0004464286,0.0007166826,0.0006013945,0.0003803105,0.0003676302,0.0005404238,0.0002578367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002742964,"about_ca_system_score_gemma":0.0001518386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008421077,"about_ca_topic_score_gemma":0.0008183246,"domain_scores_codex":[0.9989787,0.0002856345,0.0001121832,0.0001907523,0.0003494411,0.00008334353],"domain_scores_gemma":[0.9951898,0.0025215,0.0006093654,0.0006771601,0.0008582455,0.0001439695],"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":[0.002788859,0.002083497,0.008757589,0.0005388573,0.0001438576,0.0004436308,0.0006188685,0.03105831,0.8737644,0.0003676311,0.000397656,0.07903676],"study_design_scores_gemma":[0.00008644747,0.01453676,0.02182385,0.00008477818,0.0002349091,0.001073963,0.0004350182,0.152353,0.8069112,0.0005658677,0.001825146,0.00006912639],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9691102,0.000449837,0.02956849,0.00007606007,0.00009852841,0.00007068644,0.00009979733,0.0000845859,0.0004419011],"genre_scores_gemma":[0.9697508,0.0004673823,0.02830025,0.00006805923,0.00003199145,0.00009463617,0.000236739,0.00002329389,0.001026827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001699896,"threshold_uncertainty_score":0.00898999,"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."}}