{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001009923,0.0001804158,0.0004325128,0.0005568852,0.000135836,0.000019634,0.0001554628,0.0002717339,0.0003993216],"category_scores_gemma":[0.0000068222,0.0002400129,0.0004937132,0.0004698099,0.00001836271,0.0002102661,0.000009336549,0.0001428128,0.00001370205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006527457,"about_ca_system_score_gemma":0.0000272703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008242871,"about_ca_topic_score_gemma":0.0005193614,"domain_scores_codex":[0.9992707,0.00001615601,0.0001704728,0.0001772176,0.0001800779,0.0001854116],"domain_scores_gemma":[0.9994183,0.00003641551,0.0001809983,0.0001427839,0.0001245963,0.00009691457],"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":[0.0005073294,0.0005200679,0.02884077,0.01062359,0.03501494,0.00004309232,0.017602,0.004076396,0.03222042,0.0003470859,0.002629103,0.8675752],"study_design_scores_gemma":[0.001336353,0.00004314086,0.06675345,0.0003792714,0.02339363,0.000001576611,0.002170655,0.8889843,0.003152989,0.0002375925,0.01237694,0.001170165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6808797,0.0006782662,0.3131998,0.000008411891,0.0002117424,0.0001988819,0.000008818121,0.0001018036,0.004712561],"genre_scores_gemma":[0.9715964,0.0001789913,0.01795001,0.000006135202,0.00006027701,0.000002211927,0.005913717,0.00004553923,0.004246704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8849078,"threshold_uncertainty_score":0.978744,"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."}}