{"id":"W2055755947","doi":"10.1152/jn.01087.2002","title":"Task-Specific Internal Models for Kinematic Transformations","year":2003,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Canadian Institutes of Health Research","funders":"","keywords":"Task (project management); Motor learning; Kinematics; Psychology; Movement (music); Motor control; Motion (physics); Rotation (mathematics); Dynamics (music); Adaptation (eye); Communication; Contrast (vision); Cognitive psychology; Physical medicine and rehabilitation; Computer science; Artificial intelligence; Neuroscience","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":[0.00005377847,0.00008628605,0.0002050499,0.0001138774,0.00007979457,0.00002058602,0.0001670963,0.00002936415,0.0000275122],"category_scores_gemma":[0.0002303178,0.0000654843,0.0001569661,0.0000873298,0.00003981537,0.0002945152,0.000004419462,0.0001445138,0.00001024323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001233224,"about_ca_system_score_gemma":0.0000317865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.847346e-7,"about_ca_topic_score_gemma":8.900451e-8,"domain_scores_codex":[0.9990411,0.0001509061,0.0004303614,0.0001061199,0.0001197706,0.0001517119],"domain_scores_gemma":[0.9992438,0.0002568376,0.0002648047,0.00008668344,0.00008887275,0.00005901528],"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":[0.0001038648,0.00006185173,1.002459e-7,0.00001315917,0.000004014659,0.00001110435,0.0001568447,0.02179116,0.9507346,0.02612998,0.00006617323,0.0009272089],"study_design_scores_gemma":[0.01177452,0.006676967,0.00186291,0.000153786,0.0001425578,0.002657553,0.0002604383,0.4347342,0.09704358,0.3313152,0.1125735,0.0008047979],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5837084,0.00004372229,0.4127219,0.0005111913,0.001231156,0.000295112,0.00001217748,0.00001575389,0.001460569],"genre_scores_gemma":[0.997754,0.00008829373,0.001337567,0.0006028793,0.0001173492,0.000006591679,3.28678e-7,0.00001058305,0.00008235218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8536909,"threshold_uncertainty_score":0.2670372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05063097519639703,"score_gpt":0.264510980161395,"score_spread":0.2138800049649979,"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."}}