{"id":"W2914883047","doi":"10.1109/taslp.2019.2895241","title":"Differential Kronecker Product Beamforming","year":2019,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Audio Speech and Language Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Israel Science Foundation","keywords":"Kronecker product; Differential (mechanical device); Kronecker delta; Beamforming; Computer science; Product (mathematics); Subspace topology; Algorithm; Mathematics; Physics; Artificial intelligence; Telecommunications","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":[0.0001812827,0.000340712,0.0003283949,0.0002864257,0.0004498842,0.0005792412,0.0006871969,0.0001053533,0.0002334419],"category_scores_gemma":[0.00002503392,0.0002994922,0.0001025705,0.0005691427,0.00006611037,0.001228562,0.00002677957,0.000460012,0.0001523433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006010199,"about_ca_system_score_gemma":0.0001352111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002044486,"about_ca_topic_score_gemma":0.00001644915,"domain_scores_codex":[0.9977847,0.00003729561,0.0003263398,0.0008347718,0.0004214791,0.0005953796],"domain_scores_gemma":[0.9987938,0.00005304216,0.0001492188,0.000727051,0.00008495178,0.0001919564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002260631,0.00009896866,0.0001189243,0.0001423604,0.00002129907,0.00002599752,0.001663817,0.00007665407,0.09471456,0.000004286413,0.00001786023,0.9030927],"study_design_scores_gemma":[0.00102121,0.0001570333,0.0002820311,0.0003606634,0.00003954536,0.0002676324,0.0005337084,0.005061814,0.9904799,0.0002715392,0.0008670778,0.0006578602],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4099674,0.001036178,0.5864427,0.000555647,0.0005198307,0.0002651154,0.000004418013,0.0003032208,0.0009055272],"genre_scores_gemma":[0.8762179,0.00004547152,0.1214248,0.0003265213,0.0001617264,0.00001742417,0.00000305127,0.00003264664,0.001770467],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9024348,"threshold_uncertainty_score":0.9999457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009031873084287725,"score_gpt":0.2427705840847645,"score_spread":0.2337387110004768,"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."}}