{"id":"W2130786571","doi":"10.1109/icassp.2004.1326239","title":"Improving the robustness of the RARE algorithm against subarray orientation errors","year":2004,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Robustness (evolution); Estimator; Algorithm; Computer science; Orientation (vector space); Calibration; Cramér–Rao bound; Estimation theory; Mathematics; Statistics","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":[0.0002879299,0.00007864348,0.00008950052,0.00005611386,0.0001212146,0.00003989332,0.0007721348,0.00003578447,0.00000549102],"category_scores_gemma":[0.00009121047,0.00004430769,0.00006518853,0.0006095649,0.00008897616,0.0004361841,0.0001446931,0.0000757879,0.000001444327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005065848,"about_ca_system_score_gemma":0.0001115458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000206164,"about_ca_topic_score_gemma":0.00002230634,"domain_scores_codex":[0.9991389,0.00004966591,0.0002470541,0.0001627501,0.0002986165,0.0001030263],"domain_scores_gemma":[0.9990137,0.00005083324,0.0002164392,0.0005051832,0.0001931486,0.00002075014],"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":[0.000004145099,0.000153503,0.000432828,0.00007102914,0.00002694064,0.000001045144,0.003686423,0.06584149,0.01595546,0.08295488,0.000341441,0.8305308],"study_design_scores_gemma":[0.0002421514,0.00004333717,0.002478438,0.00005165951,0.000007453575,0.00000603647,0.0002739792,0.2796294,0.7139654,0.003103222,0.00007294591,0.0001260189],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02832157,0.000009232403,0.9691448,0.0005886022,0.000420476,0.0002322716,0.000001336611,0.0001688116,0.001112856],"genre_scores_gemma":[0.7201271,0.000002026126,0.2796585,0.00009171743,0.0000181472,0.00001630799,8.753366e-7,0.000005318545,0.00007995489],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8304048,"threshold_uncertainty_score":0.1806815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009953524335768961,"score_gpt":0.2363992812127344,"score_spread":0.2264457568769655,"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."}}