{"id":"W2550671001","doi":"10.1121/1.4970032","title":"Modeling wave propagation through the skull for ultrasonic transcranial Doppler","year":2016,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Attenuation; Acoustics; Attenuation coefficient; Materials science; Transcranial Doppler; Imaging phantom; Ultrasound; Amplitude; Transmission (telecommunications); Transmission coefficient; Energy (signal processing); Optics; Physics; Computer science; Medicine; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002114309,0.0007272901,0.0003626798,0.0004591214,0.0002357756,0.0006664542,0.0007030935,0.001055478,0.001658713],"category_scores_gemma":[0.0007427007,0.0004378327,0.0007808704,0.0004081625,0.0003015395,0.0006120527,0.0004408993,0.000537208,0.0006090904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004173345,"about_ca_system_score_gemma":0.0008390041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005356273,"about_ca_topic_score_gemma":0.005145793,"domain_scores_codex":[0.9999181,0.00002179154,0.00000559118,0.00001604696,0.00002874473,0.000009721163],"domain_scores_gemma":[0.9998368,0.00009255394,0.00002322202,0.00001253203,0.00002812066,0.00000676439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003985564,0.00004950456,0.0009786786,0.0001863286,0.00002943579,0.0005872253,0.0002847568,0.8945571,0.05207726,0.01362617,0.0006043934,0.03697927],"study_design_scores_gemma":[0.000006861954,0.00004447799,0.0001960669,0.00002189005,0.00001731454,0.0001685264,0.00004529658,0.9900123,0.004597011,0.001655894,0.003221352,0.00001297118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03302009,0.0007049167,0.9617321,0.0001783856,0.00006412854,0.00006772258,0.0001319533,0.00029036,0.003810293],"genre_scores_gemma":[0.5918574,0.006247046,0.3790936,0.0001965091,0.00008939574,0.000492753,0.0003678834,0.000276699,0.02137854],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005356273,"threshold_uncertainty_score":0.01065022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01854787189477472,"score_gpt":0.2608676797842401,"score_spread":0.2423198078894654,"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."}}