{"id":"W1628075215","doi":"10.1109/aps.1979.1148159","title":"An experimental nonlinear adaptive array","year":2005,"lang":"en","type":"article","venue":"","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Nonlinear system; Computer science; Control theory (sociology); Physics; Artificial intelligence","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":[0.0004395179,0.0004090616,0.000285893,0.0001435915,0.0003980624,0.0004423587,0.0006179717,0.0006763783,0.005891214],"category_scores_gemma":[0.0006817573,0.0002218441,0.000152225,0.0001994597,0.0005166525,0.0007260736,0.0005891697,0.0005134551,0.001263431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003281973,"about_ca_system_score_gemma":0.000382774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004472099,"about_ca_topic_score_gemma":0.0004702945,"domain_scores_codex":[0.9995503,0.00005770559,0.00001862519,0.0001693395,0.0001393094,0.00006475479],"domain_scores_gemma":[0.9994863,0.000127642,0.00004351856,0.0001590283,0.0001157257,0.00006776225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008246852,0.0001381685,0.0008205484,0.00006392744,0.00001380848,0.00008907024,0.00007401703,0.001262137,0.9828219,0.001619758,0.0005987957,0.01167316],"study_design_scores_gemma":[0.0002718505,0.001325715,0.00701948,0.00001674532,0.00005582962,0.0004208063,0.00008646311,0.02361053,0.9562066,0.000872424,0.01006534,0.00004827046],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8590383,0.000236509,0.1127465,0.0007873371,0.0005913828,0.0002316447,0.0009260388,0.001330885,0.02411135],"genre_scores_gemma":[0.9382282,0.0001252223,0.05091313,0.0002243466,0.00007960261,0.0001397836,0.0005591377,0.0001036088,0.009626802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005891214,"threshold_uncertainty_score":0.01970804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01262759864835551,"score_gpt":0.2378974584447103,"score_spread":0.2252698597963548,"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."}}