{"id":"W3112893815","doi":"10.3390/s20247003","title":"Indoor Positioning System Using Dynamic Model Estimation","year":2020,"lang":"en","type":"article","venue":"Sensors","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Samsung; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Universidade Federal do Amazonas","keywords":"Computer science; Computation; Node (physics); Position (finance); SIGNAL (programming language); Bluetooth; RSS; Real-time computing; Set (abstract data type); Scale (ratio); Simulation; Algorithm; Wireless; Engineering; Telecommunications","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":[0.0000255389,0.00009535457,0.0001041485,0.00005953853,0.00007045091,0.00002951055,0.00006707378,0.00008177075,0.000003605054],"category_scores_gemma":[0.00002214376,0.0001027395,0.00002990706,0.0001896684,0.0000162403,0.00008097018,0.00001494,0.00009460161,0.00003796061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001106536,"about_ca_system_score_gemma":0.000007760005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003172565,"about_ca_topic_score_gemma":5.936131e-7,"domain_scores_codex":[0.9995146,0.000007701206,0.000146975,0.0001026028,0.00009096052,0.0001372039],"domain_scores_gemma":[0.999823,0.000008151924,0.00002134889,0.00008730892,0.00002443547,0.00003578492],"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":[0.000001788406,9.128528e-7,0.00002114362,0.00008583826,0.000007962204,0.000003730291,0.000276694,0.9934099,0.004469886,0.001055157,0.00002096162,0.000645974],"study_design_scores_gemma":[0.0001057846,0.000006149319,0.00001544746,0.00003492822,0.00001227858,0.000007944413,0.0004087215,0.9906085,0.008612173,0.00006734119,0.000007062869,0.0001136437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5084954,0.00003297343,0.4890389,0.00005585804,0.00006595879,0.0000714355,0.000006706883,0.001454086,0.0007786457],"genre_scores_gemma":[0.9834311,0.000003258551,0.01646051,0.0000387104,0.00001689222,0.000002472351,0.00001184048,0.00002730909,0.000007895036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4749357,"threshold_uncertainty_score":0.4189597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01376588556201055,"score_gpt":0.2144878743723445,"score_spread":0.200721988810334,"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."}}