{"id":"W2010411145","doi":"10.1121/1.2945115","title":"Bottom-up approach for microstructure optimization of sound absorbing materials","year":2008,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Acoustic Wave Phenomena Research","field":"Engineering","cited_by":128,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Centre québécois de recherche et de développement de l’aluminium; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Tortuosity; Materials science; Absorption (acoustics); Porosity; Geometry; Lambda; Porous medium; Noise reduction coefficient; RADIUS; Physics; Mechanics; Composite material; Optics; Mathematics","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":[0.0005540834,0.0001355746,0.0003832195,0.00002225709,0.0001484302,0.0000106551,0.0005720777,0.00009261925,0.00004050686],"category_scores_gemma":[0.0001990162,0.00007707407,0.0002512844,0.0002125023,0.0006089534,0.0000693758,0.00009652673,0.0003460285,3.851204e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008066096,"about_ca_system_score_gemma":0.00006311927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009159138,"about_ca_topic_score_gemma":1.567936e-8,"domain_scores_codex":[0.9986276,0.00006901095,0.0005175633,0.0000671709,0.0004633248,0.0002553173],"domain_scores_gemma":[0.9987093,0.000385708,0.000313172,0.0002468673,0.0002859382,0.00005903685],"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":[0.0000753217,0.00002442337,0.000007904372,0.0001690353,0.0001564407,8.926926e-8,0.0008714173,0.7588874,0.2271904,0.000001608269,0.01247447,0.0001414915],"study_design_scores_gemma":[0.0006443934,0.0001497018,0.0001423691,0.00004321667,0.0002176073,0.00009960256,0.001671363,0.9741417,0.02214961,0.0005384934,0.00006955416,0.0001323751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04309067,0.0002354469,0.9557557,0.0001783126,0.0003961535,0.0002307266,0.00004389156,0.00001169161,0.00005741019],"genre_scores_gemma":[0.7476733,0.0003361351,0.2514695,0.00007312474,0.0003747949,0.000002013706,0.000001942389,0.00003086492,0.00003837732],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7045826,"threshold_uncertainty_score":0.3142989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01909833033628651,"score_gpt":0.24552419079289,"score_spread":0.2264258604566035,"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."}}