{"id":"W1919678181","doi":"10.1186/s13634-015-0276-0","title":"An efficient central DOA tracking algorithm for multiple incoherently distributed sources","year":2015,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Tracking (education); Algorithm","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":[0.0008340998,0.0008911174,0.0009740888,0.000905384,0.0005333778,0.0008141315,0.001416147,0.0007297801,0.001786572],"category_scores_gemma":[0.002163162,0.0005572713,0.0009803673,0.001222466,0.0004839039,0.00150379,0.0009395861,0.001362309,0.001223548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005192638,"about_ca_system_score_gemma":0.001510316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002706775,"about_ca_topic_score_gemma":0.003361546,"domain_scores_codex":[0.9994884,0.00006484872,0.00003257507,0.0001965937,0.0001848101,0.00003282126],"domain_scores_gemma":[0.999265,0.0002023115,0.0001098129,0.0001045566,0.000292164,0.00002604919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001707318,0.00006679337,0.00105332,0.0001991915,0.0001075531,0.00009524357,0.0002142649,0.2107825,0.04356967,0.02827541,0.002701937,0.7127635],"study_design_scores_gemma":[0.00001847495,0.00004254777,0.0003509639,0.00001385305,0.00002424659,0.0001490797,0.0000178199,0.9809923,0.008104535,0.00521079,0.005047399,0.00002797982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008408189,0.00005391303,0.9987478,0.00001114455,0.00001476055,0.000005101811,0.000006843059,0.0001383446,0.0001812641],"genre_scores_gemma":[0.04084913,0.0002088434,0.9562405,0.00004549044,0.00005197015,0.00006768109,0.0001709193,0.0001216927,0.002243844],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002706775,"threshold_uncertainty_score":0.005976617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02646591219337527,"score_gpt":0.3052598812939306,"score_spread":0.2787939691005553,"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."}}