{"id":"W2032215574","doi":"10.1155/2014/269596","title":"RFID Localization Using Angle of Arrival Cluster Forming","year":2014,"lang":"en","type":"article","venue":"International Journal of Distributed Sensor Networks","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Plan for Science, Technology and Innovation; King Saud University","keywords":"Computer science; Received signal strength indication; Radio-frequency identification; Transmission (telecommunications); Angle of arrival; SIGNAL (programming language); Communication source; Power (physics); Real-time computing; Identification (biology); Cluster (spacecraft); Transmitter; Time of arrival; Wireless; Telecommunications; Computer network; Antenna (radio)","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":[0.001062582,0.0007513486,0.00092952,0.00159055,0.0008002846,0.0009292544,0.001791749,0.0009333102,0.001010634],"category_scores_gemma":[0.003525963,0.000353899,0.0006082788,0.002812589,0.0006062906,0.001273872,0.001219098,0.0005442583,0.0006389475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00112854,"about_ca_system_score_gemma":0.001029361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006389195,"about_ca_topic_score_gemma":0.00346173,"domain_scores_codex":[0.9976935,0.0006233752,0.00008734678,0.0004239331,0.0009833948,0.0001884964],"domain_scores_gemma":[0.9975185,0.0005778826,0.0003483561,0.000487415,0.00096931,0.0000986449],"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":[0.001049647,0.0002775828,0.006588616,0.0002823627,0.0001393608,0.0002923952,0.0004991711,0.4900916,0.06317925,0.01542348,0.004212353,0.4179642],"study_design_scores_gemma":[0.00008241716,0.000555238,0.002587867,0.00001902355,0.00005784333,0.0005814542,0.000159873,0.930756,0.05248551,0.002976202,0.009630527,0.0001080277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03665507,0.0002650079,0.9579939,0.00008925992,0.0000795727,0.0001400685,0.00005777802,0.001634122,0.00308525],"genre_scores_gemma":[0.5967723,0.000406324,0.3996964,0.00009151279,0.00004484976,0.0001501943,0.0001719026,0.00007777871,0.002588697],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006389195,"threshold_uncertainty_score":0.01270401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008365022555796561,"score_gpt":0.2269436732619908,"score_spread":0.2185786507061943,"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."}}