{"id":"W2281152635","doi":"10.4271/2016-01-1850","title":"Optimization of Noise Control Treatments for Aircraft’s Sidewalls","year":2016,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Noise (video); Computer science; Noise control; Acoustics; Noise measurement; Control (management); Aerospace engineering; Engineering; Physics; Noise reduction; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000369434,0.0006067668,0.001009521,0.0001955966,0.0001361143,0.00005287505,0.0005126172,0.0006197506,0.0004045644],"category_scores_gemma":[0.0004436775,0.0004341958,0.0005267702,0.000333874,0.0003073637,0.0004722296,0.00005633744,0.0002283226,0.00007111279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003055278,"about_ca_system_score_gemma":0.00004865423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001597258,"about_ca_topic_score_gemma":0.003113501,"domain_scores_codex":[0.9968123,0.00009567167,0.001207999,0.0006549195,0.0005587254,0.0006703435],"domain_scores_gemma":[0.9975961,0.0007759688,0.0002124783,0.0009611283,0.000167282,0.0002870213],"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":[0.0004038814,0.0002123216,0.0001276359,0.00005799529,0.0001744151,0.000004907258,0.000010715,0.01318213,0.9749426,0.002713529,0.001407138,0.006762709],"study_design_scores_gemma":[0.009602488,0.002012854,0.9581602,0.0005644764,0.0003810457,0.00003029098,0.00004186486,0.00007952017,0.0008855644,0.001227211,0.02587817,0.001136329],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.597636,0.003528276,0.008400173,0.02053253,0.00392823,0.02892538,0.002829773,0.0314827,0.3027369],"genre_scores_gemma":[0.994949,0.0002149496,0.002670242,0.0003318759,0.0001369795,0.000742381,0.00003625951,0.0001475628,0.0007707898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9740571,"threshold_uncertainty_score":0.999811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0084703843236827,"score_gpt":0.2251629947124573,"score_spread":0.2166926103887746,"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."}}