{"id":"W2890924854","doi":"10.1152/jn.00182.2018","title":"Visuomotor feedback gains are modulated by gaze position","year":2018,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Gaze; Fixation (population genetics); Computer vision; Computer science; Artificial intelligence; Eye movement; Hand position; Workspace; Communication; Psychology; Robot; Medicine; Population","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":[0.00003286001,0.0001154495,0.0002261943,0.0000942382,0.0001152005,0.0000238521,0.0002089151,0.00006050108,0.000079718],"category_scores_gemma":[0.0002844527,0.00009172958,0.00009843807,0.0001545512,0.0001283617,0.0001965221,0.00002659732,0.0001918718,0.0001121039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002336561,"about_ca_system_score_gemma":0.00002477601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002697066,"about_ca_topic_score_gemma":2.166061e-7,"domain_scores_codex":[0.9988511,0.000243557,0.0003357614,0.0001907912,0.0001789009,0.000199868],"domain_scores_gemma":[0.9990181,0.0001034489,0.0004831855,0.0001262526,0.0001747822,0.00009424502],"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":[0.0002369171,0.0001040154,0.000005949882,0.000003405262,0.000004550478,0.00006135638,0.00004297785,0.000101453,0.9983007,0.00005052588,0.0003812427,0.0007068496],"study_design_scores_gemma":[0.004910387,0.0111546,0.4574973,0.0001254592,0.00008478025,0.001172888,0.00005790744,0.03517273,0.4690853,0.003449257,0.01667367,0.0006157426],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975882,0.00001077649,0.0005377863,0.0008115965,0.0008035378,0.0000785566,0.00001060573,0.00001902808,0.0001399833],"genre_scores_gemma":[0.996395,0.00004406055,0.000050185,0.002587386,0.0006592161,0.000001047126,0.000001052357,0.00001588083,0.0002461867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5292155,"threshold_uncertainty_score":0.3740624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02841891314269692,"score_gpt":0.2708714949465649,"score_spread":0.2424525818038679,"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."}}