{"id":"W4376607544","doi":"10.1109/jsait.2023.3276296","title":"Active Sensing for Two-Sided Beam Alignment and Reflection Design Using Ping-Pong Pilots","year":2023,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Huawei Technologies","keywords":"Ping pong; Reflection (computer programming); Optics; Beam (structure); Physics; Computer science; Engineering; 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":[0.0005505516,0.0008691218,0.0004639187,0.0003205567,0.0003392631,0.0006417735,0.001105424,0.0005398273,0.001335325],"category_scores_gemma":[0.00102474,0.0003486234,0.0003713297,0.0002861788,0.0003961856,0.0006798056,0.0005621398,0.0004254738,0.0004544487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003284706,"about_ca_system_score_gemma":0.0003891888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003781783,"about_ca_topic_score_gemma":0.0007321328,"domain_scores_codex":[0.9993948,0.0001818854,0.00002646413,0.0001256579,0.0002038846,0.00006735654],"domain_scores_gemma":[0.9987125,0.0004786729,0.000230755,0.0001509231,0.0003743524,0.00005287954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007181148,0.0003298101,0.001427,0.0001989133,0.00008173998,0.0001667046,0.000244004,0.02632974,0.8270416,0.00883825,0.000826424,0.1337978],"study_design_scores_gemma":[0.00008444569,0.001411925,0.0009952863,0.0000247523,0.00007949433,0.0004801076,0.00007275273,0.5625823,0.4286442,0.001933253,0.003649879,0.00004161939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08480982,0.0001517427,0.9113308,0.0001273287,0.0000665663,0.00005559282,0.00002674508,0.000542759,0.002888731],"genre_scores_gemma":[0.8233266,0.0001332832,0.1746724,0.00009126961,0.00004341282,0.00006618175,0.00003365996,0.00004190616,0.001591382],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001335325,"threshold_uncertainty_score":0.00446713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02621554688970427,"score_gpt":0.2689294828224468,"score_spread":0.2427139359327425,"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."}}