{"id":"W2266339649","doi":"10.1145/2856636.2856654","title":"Experiences with using iBeacons for Indoor Positioning","year":2016,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Beacon; Bluetooth Low Energy; Bluetooth; Computer science; Broadcasting (networking); Protocol (science); Embedded system; Real-time computing; Computer network; Wireless; 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":[0.003827321,0.001092976,0.0004384805,0.0007126381,0.00149981,0.002081844,0.001776831,0.001652069,0.01067805],"category_scores_gemma":[0.008858074,0.0004250132,0.0006062733,0.001066497,0.001047883,0.002621316,0.002160443,0.001332277,0.00534521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006096161,"about_ca_system_score_gemma":0.0005922308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006095713,"about_ca_topic_score_gemma":0.011012,"domain_scores_codex":[0.9973279,0.001370365,0.00008924195,0.0002491607,0.0006264377,0.0003368142],"domain_scores_gemma":[0.9967968,0.001148291,0.00007868941,0.0003978976,0.0009603159,0.0006179991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001335998,0.003143763,0.02221191,0.001703019,0.0001871356,0.006866891,0.1069119,0.005685742,0.03597813,0.007755666,0.05042694,0.7577929],"study_design_scores_gemma":[0.0002059626,0.005613856,0.02150631,0.0009169749,0.0003169001,0.01086133,0.04967993,0.01089449,0.03221131,0.003896684,0.8634363,0.0004600206],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5743974,0.00683502,0.2129097,0.006350933,0.001364346,0.000786608,0.001101456,0.003785058,0.1924695],"genre_scores_gemma":[0.8073412,0.005221074,0.1031007,0.001667659,0.0003264444,0.0002552927,0.001463311,0.0008915718,0.07973272],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01067805,"threshold_uncertainty_score":0.03572166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187156755547252,"score_gpt":0.2157088925860145,"score_spread":0.203837325030542,"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."}}