{"id":"W3026223917","doi":"10.1080/10255842.2020.1714226","title":"Medio-lateral stability in induced asymmetric walking","year":2019,"lang":"en","type":"article","venue":"Computer Methods in Biomechanics & Biomedical Engineering","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Institut de Readaptation Gingras Lindsay de Montreal","funders":"","keywords":"Balance (ability); Control theory (sociology); Physical medicine and rehabilitation; Stability (learning theory); Control (management); Computer science; Medicine; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.006563211,0.0003130856,0.0006997452,0.001350506,0.00006588295,0.00001642866,0.0004846256,0.0006906008,0.00005864298],"category_scores_gemma":[0.0003659884,0.0002995754,0.0001140944,0.002664957,0.00002219444,0.0001794308,0.0005016994,0.001544271,0.0000785503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005261701,"about_ca_system_score_gemma":0.0001221741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009115903,"about_ca_topic_score_gemma":0.000008864884,"domain_scores_codex":[0.995741,0.001032389,0.001178119,0.0006629074,0.0004150764,0.0009705678],"domain_scores_gemma":[0.9977494,0.001246868,0.000175128,0.0005124908,0.00006124721,0.0002548496],"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":[0.00003521151,0.0005037018,0.003206141,0.001098762,0.00003922107,0.00002909719,0.001608163,0.000006907705,0.6645116,0.001962571,0.00005264358,0.326946],"study_design_scores_gemma":[0.003906932,0.0002639719,0.08161414,0.001348412,0.0000136533,0.000006600072,0.000173864,0.9036008,0.0007128921,0.002861704,0.004802209,0.0006948063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5639376,0.0001866647,0.4272395,0.0001380363,0.007332582,0.0008252323,0.000006702269,0.0002051243,0.0001285544],"genre_scores_gemma":[0.7446457,0.00005421755,0.2543875,0.0002460858,0.0004660941,0.00008561742,0.0000415209,0.00005300362,0.00002028404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9035939,"threshold_uncertainty_score":0.9999456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03934793582580086,"score_gpt":0.3889489929138854,"score_spread":0.3496010570880845,"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."}}