{"id":"W2154259828","doi":"10.1109/aps.1989.135046","title":"Adaptive beamforming using multimode feed horn antennas","year":2003,"lang":"en","type":"article","venue":"","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Adaptive beamformer; Multi-mode optical fiber; Beamforming; Computer science; Feed horn; Electronic engineering; Bandwidth (computing); Single antenna interference cancellation; Antenna (radio); Adaptive filter; Directional antenna; Antenna array; Horn antenna; Acoustics; Algorithm; Radiation pattern; Engineering; Telecommunications; Slot antenna; Physics; Optical fiber; Decoding methods","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":[0.0002302523,0.0004801111,0.0002930156,0.0002481674,0.0001412639,0.0005829695,0.0005785203,0.0006039739,0.001626625],"category_scores_gemma":[0.0004361518,0.0002375533,0.0004418264,0.0002717297,0.000272547,0.0007730529,0.0003514954,0.0005187802,0.0009813079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004192103,"about_ca_system_score_gemma":0.0002794543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008608809,"about_ca_topic_score_gemma":0.001181335,"domain_scores_codex":[0.9998099,0.00004266652,0.000007774279,0.00002638934,0.00009490902,0.00001843672],"domain_scores_gemma":[0.9998524,0.00005131756,0.00002095404,0.00002087801,0.00004485475,0.000009597953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002173406,0.00009100683,0.001157958,0.000142138,0.00007791416,0.0001809488,0.0001345189,0.4741995,0.17437,0.1104965,0.0026759,0.2362563],"study_design_scores_gemma":[0.00001807086,0.00009341798,0.0001689708,0.00001271754,0.00001085752,0.0001180986,0.00001325522,0.9649276,0.02237554,0.005779896,0.00646201,0.0000196168],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00615423,0.00007348163,0.9907123,0.0000603435,0.00002739646,0.00001340864,0.00001883885,0.0001892612,0.002750614],"genre_scores_gemma":[0.2242363,0.0005282456,0.760455,0.0002569496,0.00005188172,0.0001348839,0.0001514364,0.00007502268,0.01411027],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001626625,"threshold_uncertainty_score":0.005441546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02413861709573642,"score_gpt":0.2148854736694974,"score_spread":0.190746856573761,"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."}}