{"id":"W4413484420","doi":"10.1038/s41598-025-97757-y","title":"Non-contact, non-visual, multi-person hallway gait monitoring","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Institute for Aging; University of Waterloo","funders":"Canadian Institutes of Health Research; Canadian Frailty Network; Canadian Space Agency; McGill University Health Centre","keywords":"Computer science; Gait; Artificial intelligence; Computer vision; Human–computer interaction; Physical medicine and rehabilitation; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000452529,0.0001760023,0.0002290813,0.0004122519,0.0002455075,0.0003797172,0.0001101577,0.00008236383,0.0001487192],"category_scores_gemma":[0.00004020773,0.0001752599,0.0001721217,0.0008019868,0.00004334659,0.0001922429,0.00002831696,0.0001602018,0.0001402689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008555769,"about_ca_system_score_gemma":0.00004833953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004077335,"about_ca_topic_score_gemma":0.00002140868,"domain_scores_codex":[0.9985381,0.00000880301,0.0003695352,0.0004867871,0.000267323,0.0003294834],"domain_scores_gemma":[0.9992405,0.00001468356,0.00006861339,0.0004422234,0.0001185896,0.000115361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000005986702,0.0003313206,0.1061161,0.0004859926,0.000529705,0.001153528,0.00152127,0.007502102,0.7664659,0.00001204837,0.07233286,0.04354318],"study_design_scores_gemma":[0.0008655041,0.00002710799,0.06681507,0.0008541719,0.0002880711,0.0000841803,0.002000183,0.1850008,0.688201,0.0002596607,0.05446565,0.001138539],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9483274,0.0002442545,0.008701631,0.00004533769,0.01612693,0.0002246012,0.00000163028,0.0003846312,0.02594355],"genre_scores_gemma":[0.9833446,0.00001000806,0.0007461613,0.00001225996,0.00008908475,0.00002881889,0.00002551436,0.00001945259,0.01572412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1774987,"threshold_uncertainty_score":0.714689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01649642876858976,"score_gpt":0.2640456363678962,"score_spread":0.2475492075993064,"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."}}