{"id":"W2094957730","doi":"10.1109/plans.2014.6851481","title":"Autonomous WLAN heading and position for smartphones","year":2014,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trusted Positioning (Canada); University of Calgary","funders":"","keywords":"Heading (navigation); GNSS applications; Computer science; RSS; Fingerprint (computing); Real-time computing; Wi-Fi; Process (computing); Compass; Global Positioning System; Hybrid positioning system; Wireless; Position (finance); Satellite system; Positioning system; Fingerprint recognition; Wireless network; Artificial intelligence; Telecommunications; Node (physics); Engineering; Geography","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":[0.00004055719,0.00004722169,0.00005541636,0.00004194564,0.00004066433,0.00001956724,0.00002652386,0.00004378398,0.00001024458],"category_scores_gemma":[0.00001450201,0.00004293073,0.00001183405,0.00003235085,0.00001171974,0.00004454698,0.000006353679,0.0000207469,0.000004922593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001172963,"about_ca_system_score_gemma":0.000001152013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003749984,"about_ca_topic_score_gemma":0.000007564016,"domain_scores_codex":[0.9997774,0.000002039932,0.00006053504,0.00005467499,0.00001931303,0.00008607421],"domain_scores_gemma":[0.9998932,0.00002423798,0.000004813042,0.00005376325,0.00001031671,0.00001368686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002313624,0.00002871916,0.00613807,0.0006042111,0.00007866305,0.000001380516,0.0009438395,0.01129135,0.0674152,0.5865214,0.01474191,0.3122121],"study_design_scores_gemma":[0.0004554069,0.00007730042,0.001814637,0.00001540703,0.00001127553,0.000009486516,0.0001330556,0.8375227,0.1292426,0.00920772,0.02127719,0.0002332858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08480905,0.00004697096,0.9080881,0.0001629591,0.0001574817,0.00009581563,0.000002738432,0.001116365,0.005520554],"genre_scores_gemma":[0.9952934,0.000008901077,0.0044453,0.00006270454,0.00003123478,0.00001306661,0.000007567535,0.000009667157,0.0001281946],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9104843,"threshold_uncertainty_score":0.1750664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004785414426405841,"score_gpt":0.1880028259211853,"score_spread":0.1832174114947794,"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."}}