{"id":"W1498555518","doi":"10.1109/icif.2003.177428","title":"Active object localization using speaker arrays","year":2003,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Object (grammar); Artificial intelligence; Speech recognition; Computer vision","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":[],"consensus_categories":[],"category_scores_codex":[0.00008980691,0.00006769594,0.00006590836,0.00004743985,0.0001152004,0.0001250933,0.0001533073,0.00002729308,0.00006132044],"category_scores_gemma":[0.00004280039,0.00005775391,0.00002219404,0.0003609823,0.00001451265,0.0005564937,0.00002566458,0.0000426039,0.00003902132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003468575,"about_ca_system_score_gemma":0.00007915992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008149538,"about_ca_topic_score_gemma":0.000003681506,"domain_scores_codex":[0.9994011,0.00002820367,0.0000824282,0.0001938555,0.0001291929,0.0001652009],"domain_scores_gemma":[0.9996839,0.00001426126,0.00003805037,0.0001667369,0.00005241398,0.00004469764],"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":[0.00002356724,0.0004645229,0.01376188,0.00009517891,0.0001255721,0.0001226076,0.007242641,0.0327046,0.2525479,0.1777483,0.003880716,0.5112824],"study_design_scores_gemma":[0.0001483838,0.00001350983,0.0001301075,0.00001270702,0.000002704882,0.00002719053,0.00007723705,0.0411567,0.9490144,0.006506944,0.002770839,0.0001393006],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009778341,0.00002985484,0.9474837,0.00004059628,0.0001507876,0.00003937663,8.078635e-8,0.00009971395,0.04237755],"genre_scores_gemma":[0.7063097,0.000002037646,0.2927741,0.0006070578,0.00002927408,8.042204e-7,3.426123e-7,0.000005159293,0.0002716087],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6965313,"threshold_uncertainty_score":0.2355136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0226995713144834,"score_gpt":0.2576042473195604,"score_spread":0.234904676005077,"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."}}