{"id":"W2151774489","doi":"10.1109/wimob.2007.4390827","title":"WLocator: An Indoor Positioning System","year":2007,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Multitude; Matching (statistics); Term (time); Wireless; Real-time computing; Map matching; Distributed computing; Global Positioning System; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003636084,0.0008229751,0.0008774324,0.001390221,0.0005532883,0.001226985,0.001820785,0.0007863902,0.01713518],"category_scores_gemma":[0.0008839803,0.0003553985,0.0003401512,0.0009180694,0.0004095575,0.001424234,0.002401529,0.0009002695,0.01322946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003146734,"about_ca_system_score_gemma":0.0006535692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001804818,"about_ca_topic_score_gemma":0.001828464,"domain_scores_codex":[0.9995016,0.00006354004,0.0000263228,0.0001133744,0.0002237672,0.00007138646],"domain_scores_gemma":[0.99968,0.00004200627,0.00003901006,0.00009449104,0.00007938275,0.00006510924],"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":[0.001594864,0.0002702137,0.004225905,0.0008093936,0.000111624,0.0008669158,0.0006262761,0.008109111,0.09194825,0.01532023,0.1554656,0.7206515],"study_design_scores_gemma":[0.0005695805,0.001502521,0.00717364,0.0001771579,0.0002836511,0.002978997,0.0002844907,0.143801,0.1218936,0.004051961,0.7169412,0.0003421173],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03213465,0.00113124,0.7279335,0.0004160906,0.0004203686,0.0007058694,0.004097469,0.177587,0.05557371],"genre_scores_gemma":[0.4329889,0.001514016,0.4594044,0.001176459,0.0004057066,0.001025507,0.01402449,0.002528383,0.08693215],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01713518,"threshold_uncertainty_score":0.05732286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004593733442186991,"score_gpt":0.2008322513386934,"score_spread":0.1962385178965064,"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."}}