{"id":"W2917144629","doi":"10.1038/s41598-019-39718-w","title":"Using smartphone accelerometry to assess the relationship between cognitive load and gait dynamics during outdoor walking","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Engineering and Physical Sciences Research Council","keywords":"Gait; Accelerometer; Physical medicine and rehabilitation; Cognition; Dynamics (music); Cognitive load; Computer science; Gait analysis; Psychology; Medicine; Neuroscience","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":[0.0002883037,0.000457722,0.0002472706,0.0008789389,0.0001932869,0.0004697489,0.0001530464,0.0003546983,0.001150063],"category_scores_gemma":[0.001334126,0.000154755,0.0002151959,0.0004321748,0.0001212646,0.0002830621,0.0003809172,0.0002348714,0.0003248871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001152955,"about_ca_system_score_gemma":0.0002164803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004589137,"about_ca_topic_score_gemma":0.01473091,"domain_scores_codex":[0.9998031,0.00004148851,0.00002459107,0.00004176982,0.00006188452,0.00002721441],"domain_scores_gemma":[0.9995962,0.00006227241,0.0001301243,0.00002130633,0.0001261881,0.0000639234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007844908,0.0008503593,0.9141262,0.0002547641,0.0002361913,0.0003020976,0.001467788,0.0003907917,0.01872064,0.00006603873,0.0006732608,0.06212746],"study_design_scores_gemma":[0.00001519395,0.0008301839,0.996646,0.00002544751,0.00004428079,0.0002094107,0.0004642424,0.0007296649,0.0006727828,0.00004474576,0.0003084614,0.000009709822],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976992,0.0001190457,0.0009275273,0.00002620418,0.00001009615,0.00005717475,0.0004084241,0.00001754592,0.0007346514],"genre_scores_gemma":[0.9962531,0.0002226893,0.00227884,0.0000431574,0.0000156328,0.00009282593,0.0003858126,0.00000462347,0.0007031831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004589137,"threshold_uncertainty_score":0.009124875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1114958759575468,"score_gpt":0.4003504860269073,"score_spread":0.2888546100693605,"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."}}