{"id":"W262433993","doi":"10.1007/978-3-662-43984-5_25","title":"Integrated Indoor Positioning with Mobile Devices for Location-Based Service Applications","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Location-based service; Service (business); Hybrid positioning system; Real-time computing; Embedded system; Telecommunications; Positioning system; Engineering","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":[0.0002064144,0.001083155,0.0006530969,0.0006351767,0.0002872956,0.001027945,0.001349306,0.001063263,0.01226422],"category_scores_gemma":[0.0003927128,0.0004270554,0.0004987576,0.001666366,0.0002127254,0.001234342,0.001200777,0.0008399384,0.008156762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003252293,"about_ca_system_score_gemma":0.0002760784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001006603,"about_ca_topic_score_gemma":0.001838236,"domain_scores_codex":[0.9996723,0.0000463171,0.00001475667,0.00006799472,0.000152159,0.00004645038],"domain_scores_gemma":[0.9998398,0.00003196581,0.000009559156,0.00004045546,0.00006671868,0.0000115089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001673525,0.00006448561,0.001068058,0.0006678679,0.00007096239,0.0003242202,0.0002131008,0.008342652,0.08641556,0.01587193,0.01932949,0.8674643],"study_design_scores_gemma":[0.00005035364,0.0009820578,0.005362173,0.0004862371,0.0004393085,0.003655737,0.0003431857,0.11754,0.1547433,0.01335334,0.7028958,0.0001485009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01226916,0.01436864,0.9035605,0.0003338017,0.0009977965,0.00007923051,0.0004452037,0.004331421,0.0636142],"genre_scores_gemma":[0.3643632,0.01686821,0.4461027,0.0005369136,0.0009941829,0.000168292,0.001897842,0.0006455983,0.168423],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01226422,"threshold_uncertainty_score":0.0410279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007296196024555677,"score_gpt":0.2118571803856097,"score_spread":0.204560984361054,"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."}}