{"id":"W2951931961","doi":"10.1007/s10439-019-02310-4","title":"Nonlinear Inversion of Ultrasonic Dispersion Curves for Cortical Bone Thickness and Elastic Velocities","year":2019,"lang":"en","type":"article","venue":"Annals of Biomedical Engineering","topic":"Ultrasonics and Acoustic Wave Propagation","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Alberta Innovates - Technology Futures; Women and Children's Health Research Institute","keywords":"Cortical bone; Ultrasonic sensor; Nonlinear system; Longitudinal wave; Inverse problem; Materials science; Inverse transform sampling; Inversion (geology); Mechanics; Mathematical analysis; Mathematics; Acoustics; Geology; Wave propagation; Physics; Optics; Surface wave; Anatomy","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":[0.0002404795,0.0001133126,0.0002579554,0.00009619374,0.00001476546,0.000005097845,0.00006806587,0.00009566367,0.0000202236],"category_scores_gemma":[0.0002968545,0.0001043704,0.00005970828,0.0001319477,0.0000657237,0.00007516792,0.00002152387,0.0001219174,0.000001985336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007761199,"about_ca_system_score_gemma":0.00001551285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003484465,"about_ca_topic_score_gemma":1.561502e-7,"domain_scores_codex":[0.9991987,0.000006137029,0.0002839665,0.0001139875,0.0002043677,0.000192862],"domain_scores_gemma":[0.9993469,0.0003601399,0.00003799904,0.00009308234,0.00007042033,0.00009148002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004858369,0.0001068821,0.0002188856,0.01125925,0.0001386639,0.000001905531,0.0002556714,0.01375057,0.9653779,0.0009955481,0.0007790801,0.007067078],"study_design_scores_gemma":[0.0004002111,0.0002230036,0.000709174,0.00116607,0.00003178082,0.000005212427,0.00006314339,0.9511526,0.04525062,0.00006231639,0.0007719796,0.0001639408],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9264697,0.002253957,0.07041468,0.0002365603,0.0002780117,0.0002031882,0.00006241831,0.00006105135,0.00002045144],"genre_scores_gemma":[0.9953926,0.001620339,0.002837989,0.00002850829,0.00004410216,0.000005070313,0.00004192528,0.0000206543,0.000008841726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.937402,"threshold_uncertainty_score":0.4256103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01191806510212177,"score_gpt":0.2277607588508478,"score_spread":0.2158426937487261,"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."}}