{"id":"W2067841796","doi":"10.1016/j.humov.2004.10.011","title":"Background visual cues and memory-guided reaching","year":2004,"lang":"en","type":"article","venue":"Human Movement Science","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":105,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Context (archaeology); Visual field; Sensory cue; Trajectory; Psychology; Visual feedback; Motor control; Computer vision; Computer science; Visual search; Object (grammar); Visual control; Visual memory; Cognition; Artificial intelligence; Cognitive psychology; Physics; 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":[0.0005060508,0.0001097893,0.00009322375,0.0001265691,0.0008554692,0.000280165,0.0002678837,0.00001672562,0.00003785059],"category_scores_gemma":[0.000115691,0.00009635845,0.00002185058,0.0002498078,0.0004571525,0.0007243975,0.000114728,0.00008100006,0.00002527042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009951495,"about_ca_system_score_gemma":0.00005490006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001535259,"about_ca_topic_score_gemma":0.00003458876,"domain_scores_codex":[0.9984201,0.00002774396,0.0001857266,0.000496699,0.0005621821,0.0003075735],"domain_scores_gemma":[0.9995793,0.00002945394,0.00008067949,0.0001664528,0.00002836973,0.0001157858],"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":[0.000002351723,0.00004138023,0.000163142,0.000004020487,4.329401e-7,0.000005534988,0.0004754284,0.0001594662,0.9533212,0.04477139,0.000006104588,0.00104956],"study_design_scores_gemma":[0.003151625,0.0005499613,0.141712,0.00009724395,0.0000149776,0.00001874693,0.0008925777,0.004319356,0.7885108,0.05947128,0.0005925169,0.0006689389],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921615,0.00001508389,0.001748861,0.0002780062,0.0001375337,0.0001936228,9.39672e-7,0.00006532673,0.005399103],"genre_scores_gemma":[0.9971315,0.000006514996,0.0003046994,0.001972434,0.00006344209,0.00001045239,4.501314e-7,0.000006418024,0.0005040541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1648104,"threshold_uncertainty_score":0.6579664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07259891739155745,"score_gpt":0.3301695944452849,"score_spread":0.2575706770537274,"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."}}