{"id":"W2098651198","doi":"10.1109/tsmcb.2004.826398","title":"Enhanced Sound Localization","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":133,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Microphone; Reverberation; Acoustic source localization; Directivity; Acoustics; Orientation (vector space); Sound localization; Ranging; Microphone array; Computer science; Sound (geography); Noise-canceling microphone; Mathematics; Physics; Sound pressure; Telecommunications; Geometry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005907186,0.001095227,0.001148555,0.001302505,0.0003431874,0.001326734,0.001517854,0.001261066,0.004860011],"category_scores_gemma":[0.002565395,0.0004848442,0.001024606,0.000967062,0.0006422422,0.002139449,0.002147132,0.001087466,0.002652797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003701618,"about_ca_system_score_gemma":0.000687453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006818784,"about_ca_topic_score_gemma":0.000988791,"domain_scores_codex":[0.9990677,0.0001344991,0.00004472881,0.0002103155,0.000480135,0.00006257104],"domain_scores_gemma":[0.9989964,0.0002820407,0.0001126161,0.0002271201,0.0003505023,0.00003131047],"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":[0.0002400868,0.00007942966,0.0007125073,0.0004537809,0.000119803,0.0003696676,0.0001473599,0.06485381,0.1182001,0.02717871,0.004498082,0.7831467],"study_design_scores_gemma":[0.00007740022,0.0003655948,0.0009421008,0.00007393635,0.0001102108,0.002096695,0.00008478057,0.8712357,0.07306172,0.0156341,0.03621729,0.0001005983],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00149667,0.0001407967,0.996991,0.00002953903,0.00004938311,0.00001585641,0.00002059397,0.0004891083,0.0007669898],"genre_scores_gemma":[0.06816901,0.0005251678,0.924665,0.0001454121,0.0001147369,0.00009582349,0.0001909798,0.0001909354,0.005902918],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004860011,"threshold_uncertainty_score":0.01625836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01668988838778912,"score_gpt":0.2359552121620396,"score_spread":0.2192653237742505,"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."}}