{"id":"W2023839579","doi":"10.1109/cscwd.2013.6581045","title":"Indoor localization of ubiquitous heterogeneous devices","year":2013,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Calibration; Signal strength; Wireless; Real-time computing; Interval (graph theory); Data mining; Telecommunications; Statistics","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":[0.0006684599,0.0006494026,0.0005493553,0.0005785956,0.000447557,0.0006926667,0.0006799113,0.0004382116,0.0008284106],"category_scores_gemma":[0.002711159,0.0001911417,0.0003305319,0.0008051405,0.0004003486,0.001010846,0.001145364,0.0002531009,0.000298378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003594824,"about_ca_system_score_gemma":0.0002348428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002187232,"about_ca_topic_score_gemma":0.001991616,"domain_scores_codex":[0.9990409,0.0003220618,0.00003153542,0.0002208373,0.0001974702,0.000187108],"domain_scores_gemma":[0.9988882,0.000439881,0.0001094102,0.0002946621,0.0002086369,0.00005925874],"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":[0.001340616,0.0003776274,0.03073218,0.0006578337,0.0002180637,0.004178143,0.000827856,0.3997282,0.1779057,0.01795117,0.002311442,0.3637711],"study_design_scores_gemma":[0.00008921633,0.001899817,0.02701426,0.00007231618,0.0002668147,0.002294093,0.0007985121,0.817157,0.1344347,0.006229421,0.009653843,0.00008995809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4689516,0.0003238826,0.5265326,0.00006999285,0.00004927633,0.00007427792,0.0000993269,0.0007602368,0.003138839],"genre_scores_gemma":[0.9747215,0.0001108106,0.02438135,0.00002068078,0.00001508695,0.00002365228,0.00005362422,0.00001560469,0.0006578036],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002187232,"threshold_uncertainty_score":0.004349053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005919289246964165,"score_gpt":0.187639275492541,"score_spread":0.1817199862455768,"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."}}