{"id":"W2767513083","doi":"","title":"Spatial components in the mental representations of numeric and symbolic magnitudes: Extending the SNARC effect","year":2009,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Cognitive and developmental aspects of mathematical skills","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Arabic numerals; Reading (process); Association (psychology); Hebrew; Representation (politics); Linguistics; Psychology; Computer science; Artificial intelligence; Politics; Law; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001258059,0.0002031556,0.0001947153,0.0007889486,0.0002055822,0.0007425277,0.000344148,0.0003462284,0.004224952],"category_scores_gemma":[0.01152485,0.0003075897,0.0001972796,0.0003933676,0.001215639,0.002006058,0.001270546,0.0006453134,0.0003436319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00021231,"about_ca_system_score_gemma":0.0002590429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001347352,"about_ca_topic_score_gemma":0.001163146,"domain_scores_codex":[0.9992719,0.0001705934,0.00003861909,0.0001760891,0.000311083,0.00003179775],"domain_scores_gemma":[0.9924399,0.004180855,0.0009038791,0.001555869,0.0007561363,0.0001634266],"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":[0.002986944,0.0004273814,0.04151597,0.0007117289,0.0002100325,0.0005376442,0.01240084,0.001733395,0.6148341,0.04331356,0.001393221,0.2799352],"study_design_scores_gemma":[0.0004277758,0.002040127,0.7465771,0.0001581589,0.0003505163,0.002378488,0.004078011,0.01260298,0.1508602,0.06511536,0.01521478,0.0001963831],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9640469,0.0002016319,0.01168959,0.0001212322,0.00002045808,0.0000324614,0.0001188198,0.0001914729,0.02357745],"genre_scores_gemma":[0.9911369,0.00008378226,0.007332507,0.000071127,0.0000107195,0.00002907774,0.00009160722,0.00005840567,0.001185809],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004224952,"threshold_uncertainty_score":0.01413387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02450585125246105,"score_gpt":0.2757132895336921,"score_spread":0.251207438281231,"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."}}