{"id":"W4414229913","doi":"10.1109/jsac.2025.3610487","title":"Polarforming Antenna Enhanced Sensing and Communication: Modeling and Optimization","year":2025,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Adelaide Research and Innovation, University of Adelaide; Guangdong Provincial Key Laboratory of Construction Foundation; National Natural Science Foundation of China","keywords":"Transceiver; Antenna diversity; Base station; Wireless; Channel (broadcasting); Exploit; Antenna (radio); Polarization (electrochemistry); Mobile telephony","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002988557,0.0001369249,0.0001759968,0.0003924946,0.0004503898,0.0001396217,0.000249106,0.00009441884,0.00000290909],"category_scores_gemma":[0.0001497086,0.0001469196,0.00001917018,0.0006664615,0.00006160458,0.0002876802,0.00005279346,0.000584556,6.813912e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001172288,"about_ca_system_score_gemma":0.0000450171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001383476,"about_ca_topic_score_gemma":0.00006779116,"domain_scores_codex":[0.9990805,0.0001563463,0.0004028784,0.0001039697,0.00008769391,0.0001685575],"domain_scores_gemma":[0.9989257,0.0002284718,0.00008705012,0.0004684877,0.0002324662,0.00005780371],"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":[0.00002182533,0.00003489017,0.0002071022,0.00001983395,0.00004367504,0.000001228958,0.0006884162,0.9857247,0.004340613,0.0006420451,0.00004563139,0.008230011],"study_design_scores_gemma":[0.000394451,0.0000141054,0.0002031499,0.0004646984,0.000019416,0.00004977923,0.000246489,0.9977416,0.0002029388,0.0004986004,0.00003479629,0.0001299676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03718695,0.003308189,0.9566121,0.0007399095,0.00008023259,0.0001547246,0.000001733998,0.0001239126,0.001792323],"genre_scores_gemma":[0.9096432,0.01700521,0.07313759,0.0001374495,0.00001501527,0.000004286743,0.00001384579,0.00001918803,0.00002416456],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8834744,"threshold_uncertainty_score":0.5991207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01605801447063482,"score_gpt":0.2523390312041879,"score_spread":0.2362810167335531,"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."}}