{"id":"W1561766660","doi":"","title":"A method for the inverse characterization of poroelastic mechanical properties","year":2002,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Composite Structure Analysis and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Poromechanics; Inverse; Materials science; Vibration; Characterization (materials science); Modulus; Mechanics; Structural engineering; Composite material; Physics; Acoustics; Mathematics; Engineering; Geometry; Porous medium; Porosity","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00004231736,0.00006188305,0.00008878781,0.00006738991,0.00005371061,0.0000208854,0.00007550722,0.00004260058,0.00009280293],"category_scores_gemma":[0.00003313447,0.00004663609,0.00003595541,0.0001284072,0.00001125285,0.00003869651,0.000003864527,0.00004351813,0.000002172271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006151172,"about_ca_system_score_gemma":0.00001661053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003877119,"about_ca_topic_score_gemma":0.003340733,"domain_scores_codex":[0.9996541,0.000007443301,0.0001214307,0.00005655077,0.00004829649,0.0001121588],"domain_scores_gemma":[0.9997092,0.00003584416,0.00002052109,0.0001049615,0.00006302122,0.00006648659],"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":[0.000001918197,0.000003278805,0.000009737701,0.00006423958,0.00007934537,7.061965e-7,0.000334724,0.5481106,0.4401969,0.0003281544,0.001730005,0.009140377],"study_design_scores_gemma":[0.00005963413,0.000009857105,0.000341808,0.000007110541,0.0001054516,0.000001677257,0.00002672183,0.9960273,0.001587752,0.00001891376,0.001756375,0.0000574218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02100251,0.00005881472,0.9782122,0.0001474006,0.0001921723,0.0001735275,0.00004581506,0.00002556639,0.0001419982],"genre_scores_gemma":[0.9900305,0.00005479544,0.009558608,0.0001116424,0.00008442657,0.000009458144,0.00002038635,0.0000153791,0.0001147966],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.969028,"threshold_uncertainty_score":0.1901765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01393311492779866,"score_gpt":0.1867503009222161,"score_spread":0.1728171859944174,"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."}}