{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001380764,0.00007927338,0.0000747787,0.0001139457,0.00006298214,0.00002897409,0.0001024922,0.00009430382,0.00003570563],"category_scores_gemma":[0.000005505822,0.00007446449,0.00001953914,0.0001731185,0.00001702421,0.0001311384,0.00001136715,0.00007472254,0.00009537263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008016299,"about_ca_system_score_gemma":0.000003760167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001198735,"about_ca_topic_score_gemma":0.00002077125,"domain_scores_codex":[0.99949,0.000003881348,0.0001474872,0.00008260549,0.00008423362,0.0001918537],"domain_scores_gemma":[0.99975,0.00001232752,0.000009542651,0.0001571766,0.00002688487,0.00004411644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002701426,0.00006583205,0.01366107,0.0004872362,0.0001138192,0.0001211546,0.001356332,0.02553179,0.03380997,0.8391809,0.004153938,0.08149088],"study_design_scores_gemma":[0.0006462506,0.0001033949,0.006132513,0.00008073032,0.00002265421,0.0001018377,0.009288945,0.1319048,0.8449618,0.0003515567,0.005702182,0.0007034219],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2428669,0.00009211909,0.6514059,0.00001027122,0.0003545366,0.00009391049,0.000001741289,0.005866041,0.09930861],"genre_scores_gemma":[0.9969994,0.000002362814,0.002805983,0.00003378159,0.00005902897,0.000003429398,0.000007736342,0.00001905486,0.0000692434],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8388294,"threshold_uncertainty_score":0.3036574,"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."}}