{"id":"W2508528761","doi":"10.1017/s0140525x16000960","title":"From “sense of number” to “sense of magnitude”: The role of continuous magnitudes in numerical cognition","year":2016,"lang":"en","type":"review","venue":"Behavioral and Brain Sciences","topic":"Cognitive and developmental aspects of mathematical skills","field":"Mathematics","cited_by":559,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Institute of Education Sciences; Vrije Universiteit Amsterdam; European Commission; University of Oxford; Kent State University; U.S. Department of Education; National Institutes of Health; National Science Foundation","keywords":"Numerosity adaptation effect; Number sense; Sense (electronics); Numerical cognition; Cognition; Cognitive psychology; Correlation; Magnitude (astronomy); Mathematics; Psychology; Cognitive science; Neuroscience; Geometry; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000705373,0.0002678407,0.00132137,0.0001267721,0.00005142373,0.00002434764,0.0002471499,0.0001194731,0.0002737602],"category_scores_gemma":[0.0006587919,0.0001391141,0.0001943482,0.0004516621,0.0006538605,0.00008418082,0.0002447651,0.0001200684,0.00001793777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001545513,"about_ca_system_score_gemma":0.0001014169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001217789,"about_ca_topic_score_gemma":0.00003821529,"domain_scores_codex":[0.9978044,0.000187767,0.000923353,0.0003458049,0.0005047775,0.0002338909],"domain_scores_gemma":[0.9961771,0.002948553,0.0004931761,0.0001651116,0.000136103,0.00007992025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002445015,0.0007712632,0.0002997302,0.001488797,0.00003163436,0.00001946961,0.000872352,4.894404e-9,0.0002928343,0.005747873,0.0001095953,0.990342],"study_design_scores_gemma":[0.001880272,0.001866054,0.002770024,0.07085277,0.001871532,0.0002190079,0.007701842,0.000004192231,0.005776877,0.8566261,0.04840115,0.002030145],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.572948,0.4143965,0.0001067373,0.0004555659,0.0001703087,0.00304709,0.001181862,0.00004364992,0.007650353],"genre_scores_gemma":[0.6192807,0.3539902,0.02551485,0.0001480436,0.0001831148,0.0002597891,0.00004023846,0.00008964737,0.0004934266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9883118,"threshold_uncertainty_score":0.5672907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07710675779932595,"score_gpt":0.3995990480083176,"score_spread":0.3224922902089917,"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."}}