{"id":"W4386715971","doi":"10.18280/isi.280412","title":"Enhancing Indoor Navigation Accuracy with a Smartphone-Based Pedometer System","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pedometer; Computer science; Smartphone application; Smartphone app; Real-time computing; Human–computer interaction; Multimedia; Physical medicine and rehabilitation; Physical activity; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002656182,0.0005009199,0.0004848373,0.0005594734,0.0001391134,0.000468013,0.0006552056,0.0004126126,0.001430184],"category_scores_gemma":[0.001009026,0.0001737014,0.0001987269,0.0003410487,0.00009569839,0.0004044904,0.0007127407,0.0002488239,0.001039165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001219811,"about_ca_system_score_gemma":0.0002269832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001274998,"about_ca_topic_score_gemma":0.001907914,"domain_scores_codex":[0.9996182,0.00006649201,0.00003177184,0.00008215877,0.0001606342,0.00004075171],"domain_scores_gemma":[0.9995294,0.00007616704,0.00004355132,0.00007227957,0.0002607842,0.00001775675],"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":[0.0009336933,0.0003235887,0.0210611,0.0009782672,0.0001262122,0.0008300853,0.0004444816,0.01620035,0.2827521,0.001344174,0.005827231,0.6691788],"study_design_scores_gemma":[0.0002566647,0.003051437,0.07285737,0.0003254155,0.0005058111,0.004171762,0.0004200965,0.577252,0.2902854,0.0008390251,0.04978102,0.0002540611],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3056166,0.0009911519,0.6778821,0.0002283181,0.0003704811,0.0002352633,0.0005950367,0.005977121,0.008103997],"genre_scores_gemma":[0.8962523,0.0003795566,0.09901203,0.0001234984,0.00006106769,0.0001079444,0.0003976499,0.0000507462,0.003615046],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001430184,"threshold_uncertainty_score":0.004784465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008768103869537249,"score_gpt":0.2063942957343607,"score_spread":0.1976261918648234,"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."}}