{"id":"W4387906670","doi":"","title":"Non Linear Inversion applied to preclinical multifrequency magnetic resonance elastography data","year":2023,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Magnetic resonance elastography; Magnetic resonance imaging; Elastography; Nuclear magnetic resonance; Inversion (geology); Geology; Physics; Radiology; Medicine; Acoustics; Seismology; Ultrasound","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":[0.0007140185,0.0005706362,0.0002927936,0.0007119876,0.0002588042,0.0007269314,0.0003406527,0.0007625562,0.003792773],"category_scores_gemma":[0.003972817,0.0001949648,0.000257998,0.0005899916,0.0003077061,0.0005331325,0.0005270063,0.0006659548,0.001059116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002154906,"about_ca_system_score_gemma":0.0007621653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001795298,"about_ca_topic_score_gemma":0.002929597,"domain_scores_codex":[0.99981,0.00005653199,0.00001540022,0.00002934156,0.00006694774,0.00002172936],"domain_scores_gemma":[0.9988332,0.000631412,0.00007758168,0.0001228028,0.0002823579,0.00005262165],"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":[0.0008038398,0.0002257138,0.002175171,0.0004710302,0.00006821043,0.0006607056,0.0002030811,0.05963978,0.6939232,0.002184911,0.001612307,0.2380321],"study_design_scores_gemma":[0.00003573438,0.0003873576,0.006976105,0.0000499848,0.00006279384,0.001362941,0.0001308771,0.6902279,0.2898332,0.00331143,0.00757535,0.00004630365],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2396607,0.0008757116,0.751783,0.0006988103,0.000156662,0.0001605868,0.0005075983,0.001525438,0.004631598],"genre_scores_gemma":[0.7536623,0.0009900529,0.2340466,0.0001907788,0.0001051241,0.0001456607,0.0009806504,0.0004495329,0.009429275],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003792773,"threshold_uncertainty_score":0.01268804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03543252170310845,"score_gpt":0.2853990821993703,"score_spread":0.2499665604962618,"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."}}