{"id":"W2610788345","doi":"10.4271/2017-01-1878","title":"Inverse Poroelastic Characterization of Open-Cell Porous Materials Using an Impedance Tube","year":2017,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Acoustic Wave Phenomena Research","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Mitacs","keywords":"Poromechanics; Materials science; Electrical impedance; Characterization (materials science); Tube (container); Porous medium; Porosity; Inverse; Acoustics; Composite material; Engineering; Physics; Nanotechnology; Electrical engineering; Mathematics; Geometry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008849686,0.000721123,0.001130965,0.0002176974,0.0005609569,0.0004939678,0.002961112,0.0006346528,0.0006360217],"category_scores_gemma":[0.0007412396,0.0006892551,0.0001597365,0.0003154053,0.001068898,0.001809788,0.001270854,0.0008083472,0.00007554153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004258956,"about_ca_system_score_gemma":0.0001445328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001317259,"about_ca_topic_score_gemma":0.006147795,"domain_scores_codex":[0.9958149,0.0001487563,0.001205128,0.0009488778,0.000862953,0.001019391],"domain_scores_gemma":[0.9961839,0.0001901473,0.0004079443,0.002596933,0.0001770356,0.000444096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002145958,0.0003256287,0.00009435574,0.0002143062,0.00003831199,0.00004511649,0.00003534645,0.0002541138,0.9969108,0.0009132047,0.0001378959,0.0008162925],"study_design_scores_gemma":[0.001196352,0.0009973673,0.9654322,0.0003154567,0.000110647,0.00007380167,0.00007614092,0.0000125703,0.02882509,0.0009519673,0.001050502,0.0009578542],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847325,0.00003946095,0.00001725276,0.000249938,0.0004247995,0.001314924,0.0002919413,0.00104052,0.01188864],"genre_scores_gemma":[0.9948543,0.0002256786,0.003757867,0.0001820645,0.0002218089,0.0001633511,0.0001296,0.0002353211,0.0002299869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9680858,"threshold_uncertainty_score":0.9995559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02999542489013124,"score_gpt":0.2855880283958428,"score_spread":0.2555926035057116,"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."}}