{"id":"W2995335241","doi":"10.3390/s20010078","title":"LocSpeck: A Collaborative and Distributed Positioning System for Asymmetric Nodes Based on UWB Ad-Hoc Network and Wi-Fi Fingerprinting","year":2019,"lang":"en","type":"article","venue":"Sensors","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Node (physics); Computer science; Ranging; Wireless ad hoc network; Computer network; Transceiver; Range (aeronautics); Positioning system; Ultra-wideband; Network topology; Real-time computing; Topology (electrical circuits); Distributed computing; Wireless; Engineering; Telecommunications; Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001267366,0.0001500087,0.0002050462,0.0001389951,0.0001338253,0.00007702308,0.00004945853,0.0001133127,0.000002653813],"category_scores_gemma":[0.00009223091,0.0001472006,0.00002581392,0.0005625946,0.00002646847,0.00004905748,0.00001963502,0.0001001303,0.000006086144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007965711,"about_ca_system_score_gemma":0.000009954136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002040495,"about_ca_topic_score_gemma":0.000002537715,"domain_scores_codex":[0.9992853,0.00002068229,0.0001672185,0.0001950187,0.00009022288,0.0002415311],"domain_scores_gemma":[0.9994527,0.0002519549,0.00004725046,0.0001318332,0.00008097065,0.00003527002],"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":[0.0000835992,0.00001075425,0.007386117,0.0005989887,0.00006590917,0.000006897627,0.0002592595,0.9793456,0.0005093722,0.005859949,0.0004123029,0.00546123],"study_design_scores_gemma":[0.000800889,0.0001095462,0.002502309,0.000315519,0.00002457698,0.000004075821,0.001504957,0.9862984,0.007022009,0.00006263189,0.00109918,0.0002559454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9360966,0.0008608172,0.05935824,0.00009440088,0.0003265792,0.0006785977,0.0001383353,0.001001158,0.001445266],"genre_scores_gemma":[0.9961407,0.0000326666,0.003655955,0.00002351382,0.00003736885,0.00001791258,0.00003877076,0.00002894998,0.00002413502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06004412,"threshold_uncertainty_score":0.6002667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003716292743357005,"score_gpt":0.1887746001806928,"score_spread":0.1850583074373358,"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."}}