{"id":"W2990619968","doi":"10.1123/jmld.2018-0040","title":"Combining Unassisted and Robot-Guided Practice Benefits Motor Learning for a Golf Putting Task","year":2019,"lang":"en","type":"article","venue":"Journal of Motor Learning and Development","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Motor learning; Task (project management); Test (biology); Physical medicine and rehabilitation; Psychology; Motor skill; Kinematics; Trajectory; Dreyfus model of skill acquisition; Rehabilitation; Robot; Computer science; Artificial intelligence; Simulation; Engineering; Medicine; Developmental psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.001460685,0.0001603684,0.00044388,0.0002511205,0.0002195838,0.00007236734,0.00004022856,0.0001023086,0.00002276497],"category_scores_gemma":[0.002920149,0.000130011,0.00009409433,0.00008910359,0.00002786295,0.0001865018,0.00004000396,0.0005317755,0.00000649162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001190468,"about_ca_system_score_gemma":0.0002715524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003852841,"about_ca_topic_score_gemma":2.736278e-7,"domain_scores_codex":[0.9984773,0.0001197724,0.0006233134,0.0002087403,0.0003398055,0.0002310134],"domain_scores_gemma":[0.9974045,0.001227303,0.0006475226,0.00005393416,0.0004623405,0.0002044192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002026168,0.0002786493,0.6472874,0.001086265,0.0008645664,0.00004382804,0.009018942,0.002177691,0.04335079,0.00008121789,0.0003502486,0.2934342],"study_design_scores_gemma":[0.009902106,0.003970968,0.5790667,0.002249629,0.0002182363,0.001563914,0.00985771,0.003357132,0.0007503416,0.00001030043,0.3886716,0.000381302],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946026,0.001857166,0.001256717,0.001062999,0.0003641176,0.0003734695,3.742927e-7,0.00002822074,0.00045434],"genre_scores_gemma":[0.9011907,0.0003202819,0.09442507,0.0002142746,0.0001438159,0.000009493362,0.000004593828,0.00003063153,0.003661115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3883214,"threshold_uncertainty_score":0.5301695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02076381466810963,"score_gpt":0.2930047521916331,"score_spread":0.2722409375235235,"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."}}