{"id":"W2038611523","doi":"10.1152/jn.01002.2010","title":"Unique characteristics of motor adaptation during walking in young children","year":2011,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Motor learning; Psychology; Adaptation (eye); Treadmill; Contrast (vision); Asymmetry; Motor skill; Physical medicine and rehabilitation; Developmental psychology; Physics; Computer science; Artificial intelligence; Neuroscience; Medicine; Physical therapy","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":[0.00004867703,0.0000805147,0.0002333952,0.0001904684,0.00002883571,0.000004593527,0.0001687268,0.00003988246,0.00001666526],"category_scores_gemma":[0.0003483904,0.00006927679,0.00006707307,0.0001160715,0.00004428303,0.0001747607,0.00002496178,0.0001988586,0.000002430051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001531685,"about_ca_system_score_gemma":0.00002827407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000317589,"about_ca_topic_score_gemma":0.000002063014,"domain_scores_codex":[0.9989601,0.0002040136,0.0004800206,0.0001159843,0.0001115731,0.0001282864],"domain_scores_gemma":[0.9991527,0.00007452161,0.0005842949,0.0000869992,0.00006569162,0.00003579685],"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":[0.0003206398,0.00007112556,0.001310829,0.000008520892,0.000003038936,0.00005040174,0.0006041325,0.00008037035,0.9962734,0.0001931773,8.500609e-8,0.001084272],"study_design_scores_gemma":[0.0004811907,0.0003980216,0.9715312,0.0000248134,0.000007103575,0.0001212301,0.00001975296,0.0008971937,0.02617209,0.0002919559,0.000001783513,0.0000537028],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993101,0.000003711136,0.0002117214,0.00001588254,0.0002882375,0.00008085206,0.000003683337,0.000005331274,0.00008047451],"genre_scores_gemma":[0.9995286,0.00007419262,0.0002073992,0.00005503318,0.0001068744,0.000001226291,3.631505e-7,0.00001019329,0.0000161197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9702203,"threshold_uncertainty_score":0.2825026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02828894876757422,"score_gpt":0.2274653608408255,"score_spread":0.1991764120732513,"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."}}