{"id":"W2005111635","doi":"10.1073/pnas.1113195108","title":"A common visual metric for approximate number and density","year":2011,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Cognitive and developmental aspects of mathematical skills","field":"Mathematics","cited_by":320,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Wellcome Trust","keywords":"Numerosity adaptation effect; Mathematics; Metric (unit); Perception; Stimulus (psychology); Density estimation; Statistics; Artificial intelligence; Pattern recognition (psychology); Statistical physics; Computer science; Physics","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":[0.001822111,0.0008393272,0.0007926351,0.003191671,0.0007113029,0.003256216,0.001457812,0.001360807,0.005291168],"category_scores_gemma":[0.02264126,0.0004533469,0.0006890962,0.002067078,0.003314867,0.006231212,0.003372919,0.001384201,0.001099934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001145055,"about_ca_system_score_gemma":0.0005320086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001401801,"about_ca_topic_score_gemma":0.0008506155,"domain_scores_codex":[0.997876,0.0006385519,0.0001761553,0.0005506102,0.0006427511,0.0001159503],"domain_scores_gemma":[0.9963169,0.001150106,0.0005951194,0.0008130444,0.0008854957,0.0002391672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003369136,0.00004536934,0.009202953,0.0005254644,0.0001160537,0.0002658724,0.001699683,0.01336171,0.04581411,0.7382385,0.008485887,0.1819075],"study_design_scores_gemma":[0.00008332272,0.0003124325,0.03883943,0.0002706484,0.00006765129,0.003594653,0.001255704,0.1328843,0.01797454,0.7391877,0.06526279,0.000266866],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03852922,0.0009762443,0.9354967,0.0009477595,0.0002077209,0.0001146585,0.0005024436,0.0009475065,0.02227767],"genre_scores_gemma":[0.5381559,0.0007333818,0.4560722,0.0004370176,0.000192446,0.0004388732,0.0005758004,0.0005112141,0.002883227],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005291168,"threshold_uncertainty_score":0.01770073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09757939228217039,"score_gpt":0.3614853836882286,"score_spread":0.2639059914060582,"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."}}