{"id":"W1998317884","doi":"10.1167/8.6.308","title":"Equivalent visuomotor adaptation for variable reach practice","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Adaptation (eye); Variable (mathematics); Visual feedback; Cognitive psychology; Psychology; Motor learning; Computer science; Artificial intelligence; Neuroscience; Mathematics","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":[0.000384798,0.0003022277,0.0004391814,0.0001971228,0.0001236885,0.0004352599,0.0004819767,0.000610636,0.002148978],"category_scores_gemma":[0.004433854,0.0002317876,0.0005528103,0.0001156869,0.0004502688,0.0004865489,0.0007306064,0.000917404,0.0002922932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004129516,"about_ca_system_score_gemma":0.0003330853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001728641,"about_ca_topic_score_gemma":0.001527068,"domain_scores_codex":[0.9996784,0.00004988897,0.00002987231,0.0001224316,0.00007017481,0.0000492014],"domain_scores_gemma":[0.9990749,0.0003610338,0.0001337352,0.0002946599,0.00006687095,0.00006881651],"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":[0.001732043,0.0008212486,0.01389847,0.0003377651,0.0002870966,0.0007225658,0.0007061404,0.272339,0.5946378,0.006039575,0.0004007985,0.1080775],"study_design_scores_gemma":[0.0001635858,0.002491969,0.06562646,0.0000443381,0.00009735587,0.001066868,0.0001119399,0.864177,0.05211609,0.01171481,0.002304994,0.00008455988],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9025109,0.0001215775,0.09391838,0.00008669566,0.00002925411,0.0001059777,0.00006946383,0.0002573332,0.002900325],"genre_scores_gemma":[0.9937481,0.00003383553,0.005310411,0.00001609278,0.000002689513,0.00006357851,0.00003851829,0.00002016491,0.0007666411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002148978,"threshold_uncertainty_score":0.007189095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03884502060212461,"score_gpt":0.3371570357421836,"score_spread":0.298312015140059,"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."}}