{"id":"W2014229377","doi":"10.1167/13.9.336","title":"The influence of crowding on grip scaling during grasping","year":2013,"lang":"en","type":"article","venue":"Journal of Vision","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Thumb; Index finger; GRASP; Perception; Computer science; Computer vision; Crowding; Artificial intelligence; Psychology; Cognitive psychology; Medicine; Anatomy","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":[0.0006082837,0.000557168,0.0005636821,0.0005066999,0.0004111091,0.0005914369,0.0003079952,0.0004242092,0.001853871],"category_scores_gemma":[0.008691575,0.0003524806,0.000320069,0.0001603145,0.0005943346,0.0007499984,0.001283271,0.0003751354,0.0002038191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000216277,"about_ca_system_score_gemma":0.0002461324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001125904,"about_ca_topic_score_gemma":0.0005950681,"domain_scores_codex":[0.9992385,0.0001359814,0.00006937632,0.0001607673,0.0002587941,0.0001366529],"domain_scores_gemma":[0.995908,0.002371805,0.0005246587,0.0003436652,0.0003715533,0.0004802332],"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":[0.00154794,0.00006784594,0.003257575,0.0002013638,0.0000223433,0.0004260103,0.0005477384,0.001356861,0.9777675,0.0001134004,0.0001262836,0.014565],"study_design_scores_gemma":[0.0002592326,0.007145412,0.5719068,0.0002251088,0.0002073822,0.002192619,0.002328356,0.02402846,0.3855907,0.00235743,0.003514931,0.0002435157],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953258,0.0004632781,0.002483442,0.00003558174,0.00003605559,0.00003521926,0.00004540197,0.00007503974,0.001500065],"genre_scores_gemma":[0.9982679,0.0001073908,0.001283057,0.00002555025,0.000009997343,0.00001921445,0.0000293717,0.00002515797,0.0002322671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001853871,"threshold_uncertainty_score":0.006201863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01773843769797629,"score_gpt":0.2927501447008891,"score_spread":0.2750117070029128,"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."}}