{"id":"W2797276369","doi":"10.1038/s41562-018-0324-5","title":"Multiple motor memories are learned to control different points on a tool","year":2018,"lang":"en","type":"article","venue":"Nature Human Behaviour","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":80,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Engineering and Physical Sciences Research Council; Canadian Institutes of Health Research; Royal Society; Wellcome Trust","keywords":"Object (grammar); Computer science; Motor control; Control (management); Association (psychology); Point (geometry); Dynamics (music); Mechanism (biology); Space (punctuation); Artificial intelligence; Psychology; Neuroscience; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005574971,0.0004900385,0.0004424472,0.0003750715,0.0003635227,0.001544965,0.001287894,0.000961212,0.005213009],"category_scores_gemma":[0.002604633,0.0005165275,0.000531323,0.0002899067,0.001445227,0.002080598,0.001319835,0.001537961,0.0007592852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003664336,"about_ca_system_score_gemma":0.0004660329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007446965,"about_ca_topic_score_gemma":0.001119509,"domain_scores_codex":[0.9995942,0.00004168589,0.00002561325,0.0001688926,0.0001071155,0.00006251071],"domain_scores_gemma":[0.9990896,0.0001791464,0.0001978233,0.000296449,0.0001233967,0.0001136348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00107088,0.0005123914,0.03478532,0.0005740745,0.0007286075,0.0007618049,0.001804802,0.01107356,0.6115338,0.03050775,0.001718376,0.3049286],"study_design_scores_gemma":[0.0002662705,0.00402614,0.4387684,0.0004633975,0.0008748936,0.003267661,0.004389106,0.102291,0.3145548,0.1134408,0.01720379,0.0004537628],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9362712,0.0004719723,0.04360743,0.0003848125,0.0001623121,0.00004463665,0.00008377326,0.0003126739,0.01866119],"genre_scores_gemma":[0.9840738,0.0002395365,0.01009769,0.0001094978,0.0000172212,0.00002781163,0.00008510001,0.00009848303,0.005250874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005213009,"threshold_uncertainty_score":0.01743931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03303872394977033,"score_gpt":0.2956193685724973,"score_spread":0.262580644622727,"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."}}