{"id":"W2890866014","doi":"10.3390/s18092970","title":"A Multi-Sensor Matched Filter Approach to Robust Segmentation of Assisted Gait","year":2018,"lang":"en","type":"article","venue":"Sensors","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Gait; Computer science; Artificial intelligence; Segmentation; Filter (signal processing); Computer vision; Physical medicine and rehabilitation; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005914136,0.0001042106,0.0001605737,0.0001419663,0.00002652594,0.00001629101,0.0000555343,0.00005153036,0.0001851541],"category_scores_gemma":[0.00001926144,0.0001001844,0.0000726292,0.0002880344,0.0000259452,0.00003355311,0.000009997152,0.00005068732,0.0002809741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002504153,"about_ca_system_score_gemma":0.000003069214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002106462,"about_ca_topic_score_gemma":0.00001773369,"domain_scores_codex":[0.9993859,0.0000235325,0.0001937034,0.0001361805,0.0001149899,0.0001456813],"domain_scores_gemma":[0.9996609,0.00001336784,0.00002857923,0.0001385853,0.00008676917,0.00007176604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005164065,0.0004098832,0.002132569,0.0003320872,0.0005942101,0.000006293852,0.005940036,0.1914675,0.7768948,0.00002039619,0.006128991,0.01602159],"study_design_scores_gemma":[0.001164389,0.00006207386,0.03239795,0.00005485609,0.0001414363,0.00001281603,0.003131463,0.7766337,0.184892,0.000006749119,0.001035676,0.0004669462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9651552,0.000005992687,0.02662134,0.00003179686,0.0000957627,0.0001404027,0.00002334677,0.0001575238,0.007768618],"genre_scores_gemma":[0.9051809,0.000002722455,0.09351563,0.00006644247,0.00006670751,0.000009653445,0.00003589946,0.00002298852,0.001098999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5920029,"threshold_uncertainty_score":0.40854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04156408159926175,"score_gpt":0.2483485702274265,"score_spread":0.2067844886281648,"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."}}