{"id":"W1968446965","doi":"10.1109/icl-gnss.2014.6934170","title":"Estimation of heading misalignment between a pedestrian and a wearable device","year":2014,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trusted Positioning (Canada)","funders":"","keywords":"Heading (navigation); Wearable computer; Computer science; Orientation (vector space); Inertial measurement unit; Wearable technology; Smart device; Real-time computing; Pedestrian; Inertial navigation system; Attitude and heading reference system; Human–computer interaction; Computer vision; Embedded system; Engineering; Transport 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":[0.0002793811,0.0008177949,0.0006057474,0.001216464,0.0002517466,0.0003656728,0.0002920562,0.0003818526,0.0007631294],"category_scores_gemma":[0.001311972,0.0002112999,0.0002442356,0.0007645703,0.0001569677,0.0003668519,0.0006445585,0.0003720298,0.0005498195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000173964,"about_ca_system_score_gemma":0.0003598205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001566861,"about_ca_topic_score_gemma":0.002163822,"domain_scores_codex":[0.9996436,0.0000601136,0.00002709948,0.00009486491,0.0001083785,0.00006609722],"domain_scores_gemma":[0.9994687,0.00009089821,0.0001275381,0.00006257145,0.0001980277,0.0000523535],"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":[0.003004726,0.0001942084,0.1645403,0.0007611308,0.0002314298,0.002121402,0.0008708882,0.0355035,0.2192149,0.001389991,0.005353246,0.5668144],"study_design_scores_gemma":[0.0001315331,0.001995533,0.3546667,0.0001467188,0.0002802429,0.004814615,0.001781593,0.5027714,0.1236109,0.00123083,0.008408951,0.0001609703],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.607511,0.001009467,0.3853809,0.000102314,0.000342213,0.00008254957,0.0004702437,0.001656794,0.003444478],"genre_scores_gemma":[0.9604602,0.0003567768,0.03795437,0.00002337105,0.00004904932,0.00002631026,0.0003188173,0.00002483689,0.0007862725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001566861,"threshold_uncertainty_score":0.003115535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01066878175928392,"score_gpt":0.2213440839355923,"score_spread":0.2106753021763084,"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."}}