{"id":"W2571995213","doi":"10.1371/journal.pone.0169924","title":"Walking on a Vertically Oscillating Treadmill: Phase Synchronization and Gait Kinematics","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"STRIDE; Treadmill; Kinematics; Physical medicine and rehabilitation; Synchronization (alternating current); Gait; Power walking; Simulation; Gait analysis; Oscillation (cell signaling); Computer science; Physical therapy; Preferred walking speed; Medicine; Physics; Telecommunications; Biology","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":[0.00008706561,0.00008581141,0.000133024,0.00003679057,0.0004529044,0.0001895344,0.0001082428,0.00003200836,0.00003034025],"category_scores_gemma":[0.003205199,0.00007641227,0.00001599367,0.00003216369,0.00005248415,0.000191267,0.00003554763,0.00006990515,0.00002350921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001960152,"about_ca_system_score_gemma":0.00001302548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006283254,"about_ca_topic_score_gemma":0.000003799532,"domain_scores_codex":[0.9991811,0.00003687518,0.000149128,0.0002145703,0.000271771,0.0001465417],"domain_scores_gemma":[0.9993556,0.0001748693,0.0001248613,0.0002449534,0.00003317969,0.00006652226],"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":[0.00004951096,0.0005977961,0.0003023004,0.00007767913,0.0000103892,0.00001212684,0.0002804279,0.00001883394,0.9683995,0.002907787,0.000003440167,0.02734026],"study_design_scores_gemma":[0.003960849,0.0007353627,0.008698202,0.0007641823,0.0001361831,0.000004393421,0.00002786672,0.7899436,0.1933927,0.001957594,0.00004153218,0.0003376113],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993829,0.000009995215,0.001702354,0.0006488673,0.00003341692,0.0002258688,0.000005320772,0.00005516119,0.003490054],"genre_scores_gemma":[0.9983098,0.00002363529,0.001096374,0.0002735312,0.00009605259,0.000009977531,0.000001419135,0.00001277035,0.0001764353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7899247,"threshold_uncertainty_score":0.3837154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08816120632469243,"score_gpt":0.2854587890922637,"score_spread":0.1972975827675713,"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."}}