{"id":"W2511126840","doi":"10.1016/j.neuropsychologia.2016.08.022","title":"Both vision-for-perception and vision-for-action follow Weber's law at small object sizes, but violate it at larger sizes","year":2016,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Università degli Studi di Parma; McGill University","keywords":"Perception; Psychology; GRASP; Object (grammar); Visual perception; Action (physics); Cognitive psychology; Computer vision; Artificial intelligence; Communication; Coding (social sciences); Task (project management); Computer science; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003691873,0.000333381,0.0003124974,0.00009581956,0.0006344597,0.0001181793,0.0002389191,0.0002104101,0.0001604394],"category_scores_gemma":[0.0006301145,0.0002297328,0.0001902686,0.0001439479,0.0001899581,0.0004049707,0.0001074343,0.000133963,0.0001998333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001078437,"about_ca_system_score_gemma":0.00001536559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002065547,"about_ca_topic_score_gemma":0.0001280102,"domain_scores_codex":[0.9974011,0.0002514214,0.0004175606,0.001125498,0.0002794353,0.000524967],"domain_scores_gemma":[0.9979521,0.001096005,0.0002486156,0.0004617014,0.00008040277,0.0001611827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001150295,0.00007229955,0.0004042497,0.00001914935,0.000005916744,0.000009299938,0.00005478757,0.000005069252,0.9726293,0.0003475498,0.002220005,0.02308206],"study_design_scores_gemma":[0.01933798,0.006223903,0.5281107,0.0002920548,0.0001661107,0.0002630944,0.00006344984,0.005112095,0.0596901,0.003427519,0.3754116,0.001901443],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895592,0.00003773805,0.00316072,0.002656503,0.001588759,0.001067081,0.0001483608,0.0002426969,0.001538986],"genre_scores_gemma":[0.9865736,0.0003177485,0.0005312376,0.004702642,0.0002607153,0.0001530233,0.00001274109,0.00006341589,0.007384845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9129393,"threshold_uncertainty_score":0.9368232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04891846118757907,"score_gpt":0.3170984732576254,"score_spread":0.2681800120700463,"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."}}