{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007224415,0.000109839,0.0002282461,0.0001752597,0.000109262,0.00008283935,0.0009675173,0.00008098933,0.00001659982],"category_scores_gemma":[0.0002114323,0.00007657723,0.00015905,0.0005445934,0.00009151299,0.0009078946,0.0001503354,0.0002389151,0.00002055865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007111464,"about_ca_system_score_gemma":0.000190049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002073829,"about_ca_topic_score_gemma":0.000008813261,"domain_scores_codex":[0.9986377,0.0000531022,0.0005649556,0.0001320911,0.0004899845,0.0001221377],"domain_scores_gemma":[0.9983692,0.00009506846,0.0007038054,0.0003811948,0.0004010381,0.00004965985],"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":[0.00006351647,0.000208279,0.00615787,0.00009788826,0.0001595357,0.000005471217,0.0008809175,0.8775151,0.007097192,0.09014756,0.003104597,0.0145621],"study_design_scores_gemma":[0.0008649817,0.000238628,0.002722277,0.0005573663,0.0000516438,0.0001490808,0.00006081328,0.7677693,0.1644987,0.01385714,0.04896295,0.000267192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2159393,0.0001122134,0.7795148,0.0004651308,0.00315556,0.0001576756,5.77379e-7,0.00006080239,0.0005939876],"genre_scores_gemma":[0.9598607,0.0000353804,0.03941306,0.0001789562,0.0001533427,0.000001921746,3.868533e-7,0.000009755003,0.0003465278],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7439214,"threshold_uncertainty_score":0.3122729,"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."}}