{"id":"W4412164102","doi":"10.1109/twc.2025.3584833","title":"Movable Antenna-Aided Near-Field Integrated Sensing and Communication","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Major Projects of Guangdong Education Department for Foundation Research and Applied Research; Guangzhou Municipal Science and Technology Project; National Natural Science Foundation of China","keywords":"Computer science; Antenna (radio); Telecommunications; Field (mathematics); Electronic engineering; Engineering; Mathematics","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":[0.000124724,0.0001773463,0.0001993327,0.0002596461,0.0007348013,0.00012116,0.000538315,0.0001845524,0.00002174456],"category_scores_gemma":[0.00001809916,0.0001911319,0.00005995929,0.0007675817,0.0002496822,0.0001652722,0.00001193399,0.0005496667,0.0000208888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009100846,"about_ca_system_score_gemma":0.00004692624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002412543,"about_ca_topic_score_gemma":0.0009120748,"domain_scores_codex":[0.9991705,0.0000928515,0.0003135331,0.0001511897,0.0000823815,0.00018959],"domain_scores_gemma":[0.9977892,0.0004238431,0.00003437871,0.001592482,0.0001226595,0.00003742007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001160011,0.0005296279,0.0004371592,0.0003747044,0.0006334237,0.000002588049,0.002609874,0.0603747,0.03098519,0.02508534,0.004839219,0.8740122],"study_design_scores_gemma":[0.0005115157,0.00002843477,0.0001306609,0.0002833866,0.000068584,0.000006391302,0.00104299,0.9192529,0.07181199,0.0009930896,0.005582202,0.0002878192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0270034,0.0008230213,0.9663382,0.001075598,0.0001750156,0.0002318063,0.00002372967,0.001244269,0.003084921],"genre_scores_gemma":[0.9786336,0.002921937,0.01784136,0.0002018786,0.000002212621,0.00006380228,0.00002036179,0.00002562237,0.0002892435],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9516302,"threshold_uncertainty_score":0.7794131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01323702294843236,"score_gpt":0.2428344517696265,"score_spread":0.2295974288211941,"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."}}