{"id":"W2544159747","doi":"10.1109/acssc.2007.4487512","title":"Optimal Beamforming with Mobile Robots","year":2007,"lang":"en","type":"article","venue":"Conference record/Conference record - Asilomar Conference on Signals, Systems, & Computers","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mobile robot; Computer science; Beamforming; Robot; Human–computer interaction; Artificial intelligence; Telecommunications","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":[0.0005456351,0.0007684217,0.0005629709,0.0003741946,0.0002386373,0.0006558735,0.0004473195,0.0007403201,0.001184585],"category_scores_gemma":[0.002085045,0.0003507994,0.000336634,0.0006322499,0.000827469,0.0009523845,0.0009218498,0.0005468884,0.0005567613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004422811,"about_ca_system_score_gemma":0.0003646361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006400623,"about_ca_topic_score_gemma":0.0007661209,"domain_scores_codex":[0.9994905,0.000220591,0.00001632035,0.0001131407,0.0001222744,0.00003715631],"domain_scores_gemma":[0.9995672,0.000247876,0.00006516588,0.00003964001,0.00006494309,0.0000151684],"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":[0.0001303773,0.00002393996,0.0006526101,0.0001348573,0.00007286004,0.00008955633,0.0001122667,0.739022,0.01374149,0.07941846,0.001806902,0.1647947],"study_design_scores_gemma":[0.0000542991,0.0001151499,0.0002965848,0.00003155929,0.00002087044,0.00008622216,0.00004117265,0.9200396,0.004653739,0.06742504,0.007210153,0.00002563204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00710664,0.0009098416,0.9889278,0.0002422728,0.00006308292,0.00001372184,0.0000168801,0.0001049922,0.002614691],"genre_scores_gemma":[0.5281631,0.003022959,0.4603156,0.0003849211,0.0002911486,0.0001604518,0.0001045753,0.00006311297,0.007494129],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001184585,"threshold_uncertainty_score":0.003962815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02756860017434402,"score_gpt":0.2513101351621163,"score_spread":0.2237415349877723,"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."}}