{"id":"W2133406022","doi":"10.11575/prism/26254","title":"Gait Analysis for Pedestrian Navigation Using MEMS Handheld Devices","year":2012,"lang":"en","type":"dissertation","venue":"PRISM (University of Calgary)","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Western Economic Diversification Canada; Ministry of Advanced Education, Government of Alberta","keywords":"Inertial measurement unit; Accelerometer; Gait; Gyroscope; Gait analysis; Inertial navigation system; Orthogonality; Computer science; Engineering; Artificial intelligence; Noise (video); Inertial frame of reference; Mathematics; Medicine; Physical medicine and rehabilitation; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.00008385246,0.0003285577,0.0002927272,0.0013329,0.0001340119,0.0002645368,0.0001547222,0.0001854921,0.00161295],"category_scores_gemma":[0.0002938672,0.00007706926,0.0005079195,0.000847223,0.00004858885,0.0001094534,0.0001704518,0.0001146282,0.0006134266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009776862,"about_ca_system_score_gemma":0.0001688909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002884599,"about_ca_topic_score_gemma":0.002781359,"domain_scores_codex":[0.9999328,0.000007829082,0.00000561714,0.00001518532,0.00002779879,0.00001085174],"domain_scores_gemma":[0.9999409,0.000009809307,0.00001192051,0.000005900013,0.0000251297,0.000006301181],"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":[0.0008772528,0.0002152418,0.04333887,0.0005717814,0.0001978833,0.0009492044,0.0002307211,0.04650326,0.1196423,0.001447408,0.005058584,0.7809675],"study_design_scores_gemma":[0.00004372562,0.0008093527,0.2364162,0.0001518287,0.0001604734,0.001039864,0.0004051428,0.7238941,0.02784455,0.001011034,0.008166451,0.00005737317],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6377291,0.001329436,0.3530317,0.00008009249,0.0001892928,0.0002498196,0.001688513,0.001343726,0.004358272],"genre_scores_gemma":[0.9269136,0.000671835,0.06776728,0.00002968731,0.00004603957,0.0001380407,0.001423577,0.00002760777,0.002982254],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002884599,"threshold_uncertainty_score":0.005735695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01799697893902487,"score_gpt":0.2237005295169473,"score_spread":0.2057035505779225,"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."}}