{"id":"W4381158217","doi":"10.1016/j.autcon.2023.104981","title":"Two-stage clustering for improve indoor positioning accuracy","year":2023,"lang":"en","type":"article","venue":"Automation in Construction","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ericsson (Canada); University of Regina","funders":"","keywords":"Cluster analysis; Computer science; Process (computing); Matching (statistics); Data mining; Fingerprint (computing); Positioning technology; Key (lock); Artificial intelligence; Real-time computing","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":[0.0001563987,0.0001083941,0.0001138786,0.0004080544,0.0001078028,0.00006640248,0.00007813884,0.0001061985,0.0000203826],"category_scores_gemma":[0.0001485937,0.0001270692,0.00003768907,0.0005621547,0.00003517847,0.0003965963,0.00002403828,0.00009891093,0.0000400994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001245659,"about_ca_system_score_gemma":0.00001499781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001525932,"about_ca_topic_score_gemma":0.00002512429,"domain_scores_codex":[0.9992423,0.00001274633,0.0002999828,0.0001449812,0.00009288571,0.0002071115],"domain_scores_gemma":[0.9996395,0.0001011849,0.00005953322,0.0001307061,0.0000507638,0.00001830021],"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":[0.0000268367,0.00001197511,0.005987574,0.0005227116,0.0000489527,0.000004407037,0.0009353628,0.5670264,0.05421409,0.03680582,0.0006622136,0.3337536],"study_design_scores_gemma":[0.0007619032,0.00001526884,0.00247475,0.00004699329,0.00000563871,0.000008371868,0.0008741719,0.9525186,0.04056971,0.00203335,0.0005255304,0.0001656714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5793782,0.00002134013,0.412206,0.0001336717,0.001737742,0.0005685322,0.00003645285,0.004484037,0.001433983],"genre_scores_gemma":[0.9895254,0.0000231122,0.01000508,0.00001643785,0.00007307217,0.0001789562,0.0001034941,0.00002589024,0.00004860304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4101471,"threshold_uncertainty_score":0.5181733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01172317859910958,"score_gpt":0.2619654110625235,"score_spread":0.2502422324634139,"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."}}