{"id":"W2019653969","doi":"10.1115/dscc2013-3895","title":"Investigation of the Suitability of Utilizing Permutation Entropy to Characterize Gait Dynamics","year":2013,"lang":"en","type":"article","venue":"","topic":"Chaos control and synchronization","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Robustness (evolution); Sample entropy; Computer science; Treadmill; Gait; Nonlinear system; Repeatability; Gait analysis; Artificial intelligence; Physical medicine and rehabilitation; Mathematics; Pattern recognition (psychology); Statistics; Medicine; Physical therapy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001306763,0.0003298451,0.0002231966,0.0007380839,0.000120887,0.0003650008,0.000166357,0.0002511906,0.0005744934],"category_scores_gemma":[0.005982184,0.00009621686,0.0001953008,0.0004448247,0.0002973534,0.0006155411,0.0003452257,0.0002492211,0.0001164618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006714876,"about_ca_system_score_gemma":0.0001522961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003621729,"about_ca_topic_score_gemma":0.0005359182,"domain_scores_codex":[0.9995826,0.0001964528,0.0000258002,0.00008023602,0.00008696415,0.00002783449],"domain_scores_gemma":[0.9960902,0.003148858,0.0002187799,0.0002247701,0.0002484339,0.00006898536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001622784,0.000339031,0.1173192,0.0003054155,0.0003976415,0.0004902894,0.0008206794,0.03519691,0.5123093,0.003104315,0.0003724433,0.3277221],"study_design_scores_gemma":[0.00004343608,0.003123093,0.3983048,0.00003771896,0.0002294,0.001454892,0.0004496419,0.4359112,0.1551229,0.003633684,0.001539903,0.0001492962],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9048733,0.0002429231,0.09303644,0.00006157648,0.00002750779,0.00004927274,0.0001674753,0.00007974564,0.001461714],"genre_scores_gemma":[0.9840798,0.00009669233,0.01551847,0.000005833434,0.00001462023,0.00002007039,0.00009486979,0.00001018148,0.0001594731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001306763,"threshold_uncertainty_score":0.006910861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01220578010649635,"score_gpt":0.2090291655752388,"score_spread":0.1968233854687425,"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."}}