{"id":"W2315110510","doi":"10.1037/a0033580","title":"Reading is fundamentally similar across disparate writing systems: A systematic characterization of how words and characters influence eye movements in Chinese reading.","year":2013,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Reading and Literacy Development","field":"Psychology","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institutes of Health; Chinese Academy of Sciences; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Reading (process); Writing system; Scripting language; Psychology; Word recognition; Linguistics; Chinese characters; Eye movement; Character (mathematics); Cognitive psychology; Computer science; Artificial intelligence","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":[0.001067867,0.0002715704,0.0002552696,0.0005732613,0.0002161511,0.0004558227,0.000218063,0.0002261929,0.0008025664],"category_scores_gemma":[0.007354754,0.0002331423,0.0003999062,0.000323538,0.0008388598,0.0005708141,0.0006478729,0.000353361,0.00008278307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003255851,"about_ca_system_score_gemma":0.000402824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004388506,"about_ca_topic_score_gemma":0.006471389,"domain_scores_codex":[0.9994311,0.0002045652,0.00003508031,0.0002001659,0.00008929617,0.00003986475],"domain_scores_gemma":[0.9965689,0.002110327,0.0006709319,0.000428157,0.0001228264,0.00009880045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008133229,0.0003380919,0.5159071,0.0003636867,0.0006092222,0.000408796,0.008906541,0.001805337,0.3904783,0.00173935,0.0002930541,0.07833719],"study_design_scores_gemma":[0.000006526264,0.0001018468,0.9943877,0.000006233067,0.00004768235,0.00004342335,0.0002334212,0.001092205,0.003660491,0.0003035609,0.0001077877,0.000009196259],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975345,0.0001177737,0.001321285,0.00002419422,0.000003902508,0.00001970049,0.00007524285,0.00002391727,0.0008794114],"genre_scores_gemma":[0.9989265,0.00004178597,0.0007834107,0.00001342395,0.000001821733,0.00001870255,0.00007026635,0.00001026466,0.0001338612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004388506,"threshold_uncertainty_score":0.008725941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01575639318029372,"score_gpt":0.3513295416726554,"score_spread":0.3355731484923617,"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."}}