{"id":"W3135438529","doi":"10.1016/j.ultras.2021.106406","title":"Noninvasive calibrated tissue temperature estimation using backscattered energy of acoustic harmonics","year":2021,"lang":"en","type":"article","venue":"Ultrasonics","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Michael's Hospital; Toronto Metropolitan University","funders":"","keywords":"Materials science; Ultrasound; Acoustics; Scanner; Harmonics; Ultrasonic sensor; Attenuation; Temperature measurement; Calibration; Thermocouple; Harmonic; Energy (signal processing); Radio frequency; Biomedical engineering; SIGNAL (programming language); Speed of sound; Optics; Physics; Medicine; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00007807445,0.0002085684,0.0003836355,0.0001213934,0.00009247726,0.0000454017,0.00007977935,0.00017901,0.0001520383],"category_scores_gemma":[0.0003029015,0.0002019078,0.0001263077,0.0007463493,0.0001018543,0.0001270196,0.00002087357,0.0002557057,0.000007670656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006033659,"about_ca_system_score_gemma":0.0004673321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008122742,"about_ca_topic_score_gemma":0.00002300205,"domain_scores_codex":[0.9987044,0.00005988162,0.0003419627,0.000317186,0.0002791375,0.0002973744],"domain_scores_gemma":[0.9987687,0.0001723419,0.0001364551,0.0003878456,0.0003875962,0.000147065],"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":[0.00003531935,0.0001894532,0.002240706,0.0001590472,0.0001472877,0.00006020616,0.0003396227,0.003815928,0.9910848,0.0001235386,0.0009780993,0.0008259669],"study_design_scores_gemma":[0.001637008,0.0002167476,0.002081706,0.0006515086,0.0006673948,0.002165098,0.0007314309,0.02097295,0.9645798,0.000192047,0.005698528,0.0004058467],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9473575,0.001876105,0.04909652,0.0005469781,0.0003541594,0.0001286736,0.00007129518,0.0001094558,0.0004592945],"genre_scores_gemma":[0.9585763,0.0002587508,0.03971237,0.0005908901,0.00007779433,0.000003985897,0.0003199493,0.00004510572,0.000414808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02650509,"threshold_uncertainty_score":0.8233563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01236065754296175,"score_gpt":0.2597829707709433,"score_spread":0.2474223132279815,"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."}}