{"id":"W2909860276","doi":"10.1016/j.jfranklin.2019.01.019","title":"Mixed rectilinear sources localization under unknown mutual coupling","year":2019,"lang":"en","type":"article","venue":"Journal of the Franklin Institute","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Science Foundation of Ningbo Municipality; National Natural Science Foundation of China","keywords":"Coupling (piping); Range (aeronautics); Mutual information; Cramér–Rao bound; Computer science; Algorithm; Field (mathematics); Mathematics; Topology (electrical circuits); Estimation theory; Artificial intelligence; Engineering; Combinatorics","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":[0.0006735913,0.0008175954,0.0006417402,0.0006432658,0.0003048318,0.000925291,0.0005568924,0.0008655921,0.0008367961],"category_scores_gemma":[0.003550337,0.000552693,0.0004049168,0.0009787313,0.0007207161,0.001645837,0.001751255,0.0006621381,0.0003977163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003009321,"about_ca_system_score_gemma":0.0004385806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007555762,"about_ca_topic_score_gemma":0.001068866,"domain_scores_codex":[0.9995039,0.0001674743,0.00002000279,0.0001110813,0.0001595397,0.0000380778],"domain_scores_gemma":[0.998919,0.0005363371,0.0002229322,0.0001248689,0.0001658001,0.00003113131],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000918821,0.00007241582,0.005068691,0.0003070758,0.0002744488,0.0008263221,0.0004947878,0.5647835,0.09412019,0.1232384,0.002582119,0.2073132],"study_design_scores_gemma":[0.00001827697,0.00004403752,0.0007479517,0.00001288063,0.00003223735,0.0002628584,0.00004563152,0.9756913,0.008238252,0.01375462,0.001124856,0.00002707536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03948107,0.0002947426,0.9579521,0.0002004233,0.0000354473,0.000007317614,0.00004396741,0.0001194812,0.001865511],"genre_scores_gemma":[0.7137595,0.0008480578,0.2793189,0.00008923958,0.00009641363,0.00004892818,0.0001924722,0.00007556674,0.00557088],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.000925291,"threshold_uncertainty_score":0.003562331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01950672972248228,"score_gpt":0.2494044923240239,"score_spread":0.2298977626015416,"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."}}