{"id":"W2108354294","doi":"10.1109/mwscas.2007.4488760","title":"A spatial exploration based blind DOA estimation algorithm for closely spaced sources","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Extrapolation; Algorithm; Computer science; Correlation coefficient; Block (permutation group theory); Mean squared error; Coefficient matrix; Computational complexity theory; Mathematics; Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000813288,0.0001719255,0.000202028,0.0003387633,0.0001314487,0.0002855996,0.000464627,0.0001151928,0.00001006253],"category_scores_gemma":[0.0003269901,0.0001756256,0.00006610463,0.0004660272,0.00007072842,0.001576052,0.00006069682,0.00009540083,0.000007479749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005622369,"about_ca_system_score_gemma":0.0001491763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004456282,"about_ca_topic_score_gemma":0.000008212944,"domain_scores_codex":[0.9985819,0.000007301459,0.0004236133,0.0003757194,0.0003605246,0.0002509273],"domain_scores_gemma":[0.9981623,0.0001176958,0.0003983864,0.0001482753,0.001083208,0.00009008084],"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":[0.0000475293,0.00009315256,0.0002175802,0.00009641883,0.00001014669,3.990379e-7,0.002092081,0.00004143689,0.008790758,0.03922551,0.0003016426,0.9490833],"study_design_scores_gemma":[0.000414074,0.0001866025,0.0002815456,0.0000668179,0.000008336785,0.00000167897,0.0000758025,0.7003568,0.2814906,0.01666455,0.0003017511,0.0001514013],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009382175,0.00000651887,0.9877754,0.000554963,0.0001766614,0.0006734774,0.000003663077,0.0005346549,0.0008924815],"genre_scores_gemma":[0.5100042,0.000001382169,0.4897872,0.00004208778,0.00004032789,0.00007827625,0.000007195018,0.000007939877,0.00003139541],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9489319,"threshold_uncertainty_score":0.7161803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04322867996489723,"score_gpt":0.3015852059163894,"score_spread":0.2583565259514922,"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."}}