{"id":"W2542911659","doi":"10.3758/s13414-016-1221-5","title":"Big and small numbers: Empirical support for a single, flexible mechanism for numerosity perception","year":2016,"lang":"en","type":"article","venue":"Attention Perception & Psychophysics","topic":"Cognitive and developmental aspects of mathematical skills","field":"Mathematics","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Numerosity adaptation effect; Perception; Object (grammar); Mathematics; Computer science; Artificial intelligence; Pattern recognition (psychology); Neuroscience; Psychology","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":[0.002343597,0.0004567805,0.0005881728,0.0009932285,0.0003965487,0.003411738,0.001370824,0.001571059,0.01286166],"category_scores_gemma":[0.03139429,0.0008075105,0.0005004277,0.0005482067,0.003136128,0.005358602,0.002365441,0.001349088,0.001023524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003540895,"about_ca_system_score_gemma":0.0005188034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001093962,"about_ca_topic_score_gemma":0.0007131209,"domain_scores_codex":[0.9988373,0.000155541,0.0000728313,0.0005236588,0.0002995153,0.0001111695],"domain_scores_gemma":[0.980693,0.01281908,0.002122822,0.002875841,0.0007879886,0.0007012875],"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":[0.003541884,0.0007897391,0.1297978,0.001324243,0.0003831076,0.0008046335,0.008402563,0.005587283,0.2921942,0.2783086,0.006425815,0.2724402],"study_design_scores_gemma":[0.000394659,0.0003588613,0.5892357,0.0001955633,0.000145476,0.001584089,0.001460944,0.02844964,0.01828972,0.3551435,0.004514803,0.0002270085],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8791524,0.0005929166,0.07180154,0.001443916,0.0001716464,0.0001208488,0.0004870489,0.0002747066,0.04595498],"genre_scores_gemma":[0.9888303,0.000111449,0.009172636,0.0002583655,0.00004126639,0.00007081125,0.0001505111,0.0001262589,0.001238392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01286166,"threshold_uncertainty_score":0.04302657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1059259964101237,"score_gpt":0.3517522846269621,"score_spread":0.2458262882168384,"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."}}