{"id":"W4362496313","doi":"10.1109/lra.2023.3264199","title":"Multidirectional Human-in-the-Loop Balance Robotic System","year":2023,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Balance (ability); Robot; Computer science; Tracking (education); Trajectory; Simulation; Control theory (sociology); Artificial intelligence; Computer vision; Physical medicine and rehabilitation; Control (management); Psychology; Physics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002783827,0.0005190211,0.0002861436,0.0002185255,0.000292905,0.0004793589,0.0007165393,0.0006478359,0.004189065],"category_scores_gemma":[0.0004122421,0.0002144221,0.0002028409,0.00009072537,0.0002247624,0.0004616281,0.0009053145,0.0002748799,0.001108761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001085223,"about_ca_system_score_gemma":0.0003068325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006164091,"about_ca_topic_score_gemma":0.0006530997,"domain_scores_codex":[0.999769,0.00002461134,0.00001658856,0.00006475963,0.00009324355,0.00003186306],"domain_scores_gemma":[0.9998075,0.00002810737,0.00004645183,0.00003519025,0.00004594048,0.00003679882],"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":[0.0006863078,0.0002947628,0.002204063,0.0005005876,0.00008379747,0.0006822787,0.0003607633,0.02670863,0.7598667,0.002445868,0.002671983,0.2034942],"study_design_scores_gemma":[0.0003998368,0.005568982,0.01997688,0.0001397975,0.0002249488,0.00292047,0.0001758065,0.67361,0.249749,0.003092254,0.04390251,0.0002395166],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2294735,0.000467112,0.7511773,0.0002588367,0.000208728,0.0004149533,0.000214572,0.004781963,0.01300318],"genre_scores_gemma":[0.8783565,0.0001548946,0.1129059,0.0001595443,0.00005259436,0.0003332722,0.0001412104,0.00005783223,0.007838268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004189065,"threshold_uncertainty_score":0.01401383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03295116870902059,"score_gpt":0.3359980158478225,"score_spread":0.3030468471388019,"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."}}