{"id":"W3021111486","doi":"10.1016/j.humov.2020.102625","title":"Grasping a 2D virtual target: The influence of target position and movement on gaze and digit placement","year":2020,"lang":"en","type":"article","venue":"Human Movement Science","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Gaze; Computer vision; Numerical digit; GRASP; Artificial intelligence; Thumb; Computer science; Movement (music); Psychology; Communication; Mathematics; Anatomy; Physics; Medicine","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":[0.0003225843,0.0001431788,0.0001283945,0.00007572281,0.0005496067,0.000155327,0.000287936,0.00001675014,0.00002649232],"category_scores_gemma":[0.0001728329,0.0001054823,0.00002287197,0.0002814413,0.000533606,0.0004280793,0.0001776864,0.00009486472,0.000004326175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000416763,"about_ca_system_score_gemma":0.00003672244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002065062,"about_ca_topic_score_gemma":0.000001649306,"domain_scores_codex":[0.9981596,0.00004732253,0.0002723817,0.0005115394,0.0007461658,0.0002629895],"domain_scores_gemma":[0.9994124,0.00007025999,0.0001694821,0.0001711497,0.00004371018,0.0001329835],"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":[0.00003129167,0.00004766428,0.0008306878,0.00001354674,0.000002053697,0.000002228385,0.001297564,0.008402132,0.9599059,0.0290316,0.00001271286,0.0004226419],"study_design_scores_gemma":[0.001804521,0.002796875,0.1993504,0.0001556263,0.00001733798,0.000001369269,0.0008010237,0.04270007,0.7422844,0.009305303,0.0003451285,0.0004380496],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959989,0.00002053262,0.001344244,0.001600605,0.00003993962,0.0005010318,0.000008942945,0.00002534782,0.0004605197],"genre_scores_gemma":[0.988681,0.0000161643,0.000086705,0.01109997,0.00002973041,0.00002993374,0.000001075994,0.000006145744,0.00004934522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2176215,"threshold_uncertainty_score":0.4301443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02443780844039067,"score_gpt":0.2489583297337648,"score_spread":0.2245205212933742,"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."}}