{"id":"W2084638580","doi":"10.4028/www.scientific.net/amm.543-547.2201","title":"A Review of Super-Resolution Methods for Nonorthogonal Analysis of Highly Correlated Signals in Noise","year":2014,"lang":"en","type":"review","venue":"Applied Mechanics and Materials","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities; Central University of Technology","keywords":"Noise (video); Resolution (logic); Computer science; SIGNAL (programming language); High resolution; Electronic engineering; Algorithm; Artificial intelligence; Engineering; Remote sensing; Geology; Image (mathematics)","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":[0.0009295536,0.001242278,0.001429707,0.004018709,0.000374326,0.0009330827,0.001387146,0.001268279,0.004108579],"category_scores_gemma":[0.001535781,0.0006330826,0.0007672123,0.004538856,0.0006036935,0.001881338,0.0007521058,0.001472408,0.002969329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004658563,"about_ca_system_score_gemma":0.0009737024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009744169,"about_ca_topic_score_gemma":0.00113341,"domain_scores_codex":[0.9996042,0.00005499786,0.00004868745,0.00007584726,0.0001917214,0.00002459197],"domain_scores_gemma":[0.9989802,0.0005372511,0.0001007434,0.00004652871,0.000296178,0.0000390799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003829284,0.00007282974,0.0002052304,0.01533972,0.0001039622,0.0002074075,0.00006887382,0.001136101,0.005084697,0.008428898,0.01850953,0.9508044],"study_design_scores_gemma":[0.00001581086,0.0001579309,0.001251178,0.003390401,0.0001848788,0.002512477,0.00006967044,0.002310619,0.005361854,0.007364043,0.9772684,0.0001128041],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003043607,0.9868811,0.009494481,0.0002888663,0.0002981265,0.00002174833,0.00005539819,0.00005652359,0.002599322],"genre_scores_gemma":[0.002180031,0.9867157,0.008955558,0.0002172467,0.0004150228,0.00003275137,0.00009431806,0.00001584891,0.001373495],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004108579,"threshold_uncertainty_score":0.01374453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03641907020040838,"score_gpt":0.3730551877931088,"score_spread":0.3366361175927004,"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."}}