{"id":"W2152233657","doi":"10.1109/glocom.2010.5683630","title":"Received Signal Compensation-Based Position Estimation of Outdoor RFID Nodes","year":2010,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Compensation (psychology); Position (finance); Computer science; SIGNAL (programming language); Estimation; Engineering; Business","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":[0.0002858077,0.0005270204,0.000563094,0.0007047162,0.0002787768,0.0004079873,0.0009625151,0.0004044957,0.0006301437],"category_scores_gemma":[0.001025331,0.0002584769,0.0002606607,0.0005501523,0.0002743241,0.0006273038,0.0003629119,0.0002737047,0.0008313884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003412879,"about_ca_system_score_gemma":0.0004547652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001718885,"about_ca_topic_score_gemma":0.001981188,"domain_scores_codex":[0.9996628,0.00006093519,0.00001408333,0.0000836504,0.0001459656,0.000032667],"domain_scores_gemma":[0.9996303,0.0000756146,0.00009162245,0.00005164238,0.0001341831,0.00001659257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003339701,0.00009889618,0.008050373,0.0002030433,0.00007872083,0.0003194407,0.0001625418,0.2720977,0.1507878,0.004802187,0.002455521,0.5606098],"study_design_scores_gemma":[0.00003676372,0.0001987923,0.003213339,0.00001767076,0.00004014089,0.000392085,0.00003463147,0.9250628,0.06482036,0.0008752914,0.005260386,0.00004786372],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03513361,0.0003120495,0.9617007,0.00005787759,0.00006079824,0.00001841102,0.0000357103,0.0009862235,0.00169474],"genre_scores_gemma":[0.6547727,0.0002895587,0.3406742,0.00006687944,0.00007980624,0.00006480379,0.0001831299,0.00005604493,0.00381293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001718885,"threshold_uncertainty_score":0.00341773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005867800412140932,"score_gpt":0.2077751449766504,"score_spread":0.2019073445645095,"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."}}