{"id":"W4400114560","doi":"10.1109/i2mtc60896.2024.10561013","title":"Multi-Level Method for Sound Source Location Measurement","year":2024,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Carleton University","funders":"","keywords":"Computer science; Sound (geography); Acoustics; Physics","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":[0.0006393797,0.0005765062,0.0006236222,0.001021311,0.0003689148,0.0008728132,0.001423456,0.001137439,0.008326387],"category_scores_gemma":[0.002238331,0.0004616571,0.0007395257,0.001054282,0.0003897413,0.001272128,0.00155638,0.001150859,0.00403073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000521386,"about_ca_system_score_gemma":0.001042757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001206045,"about_ca_topic_score_gemma":0.002252138,"domain_scores_codex":[0.9989582,0.0001948242,0.00004274889,0.0001604536,0.0005992473,0.00004451022],"domain_scores_gemma":[0.9992688,0.0002196542,0.000068049,0.0001631889,0.000243027,0.00003725997],"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":[0.0002694268,0.0001188938,0.001112123,0.0005274304,0.0001306166,0.0001385882,0.0002420529,0.09419099,0.1378173,0.02542413,0.006113689,0.7339147],"study_design_scores_gemma":[0.00004307888,0.00008935716,0.0007956694,0.00004106023,0.00003127922,0.0002833356,0.00003566184,0.9462215,0.02772211,0.006162038,0.01851308,0.00006177058],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007163621,0.00007187229,0.9980652,0.00002327411,0.00001960058,0.00001826339,0.00003137055,0.0003810364,0.0006730103],"genre_scores_gemma":[0.03673797,0.0001149215,0.9604519,0.00008285756,0.00001925547,0.0001206381,0.0001355295,0.0001470658,0.002189739],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008326387,"threshold_uncertainty_score":0.0278545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1548863940552345,"score_gpt":0.353975392425714,"score_spread":0.1990889983704794,"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."}}