{"id":"W2073774594","doi":"10.1167/10.7.1064","title":"Sequence effects during manual aiming: A departure from Fitts's Law?","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":"University of British Columbia","funders":"","keywords":"Movement (music); Task (project management); Sequence (biology); Computer science; Interval (graph theory); Trajectory; Artificial intelligence; Fitts's law; Equidistant; Algorithm; Cognitive psychology; Mathematics; Psychology; Geometry; Engineering","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":[0.003247659,0.000696675,0.001470547,0.001044985,0.0004347691,0.00115197,0.001971105,0.001551341,0.005192555],"category_scores_gemma":[0.02185599,0.0007961565,0.001733016,0.0007675809,0.002734927,0.002978936,0.001294135,0.001983341,0.001113695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009953328,"about_ca_system_score_gemma":0.0007152587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003499544,"about_ca_topic_score_gemma":0.001723622,"domain_scores_codex":[0.9979053,0.0002858764,0.0001513839,0.0007739921,0.0007466231,0.0001368504],"domain_scores_gemma":[0.992025,0.005531343,0.0007581546,0.001077807,0.0004477886,0.0001598132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002654942,0.0003513202,0.0254321,0.001832396,0.0004904376,0.001887702,0.004815821,0.05729261,0.1332108,0.3621257,0.004065902,0.4058404],"study_design_scores_gemma":[0.0004839152,0.002214643,0.1263659,0.0004035477,0.0003592135,0.004864949,0.000316173,0.1625064,0.02859013,0.647169,0.02621822,0.0005078306],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3022783,0.0130984,0.6328768,0.003231521,0.0007128702,0.0003111411,0.0006028517,0.001613665,0.04527443],"genre_scores_gemma":[0.9149448,0.003518915,0.06991426,0.001555395,0.00045289,0.0005138672,0.0004110419,0.0006398784,0.008049029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005192555,"threshold_uncertainty_score":0.01737082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01617597290130398,"score_gpt":0.2905327945296182,"score_spread":0.2743568216283143,"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."}}