{"id":"W2390297378","doi":"","title":"Effect of Word Segmentation Cues on Japanese-Chinese Bilingual's Chinese Reading:Evidence from Eye Movements","year":2011,"lang":"en","type":"article","venue":"","topic":"Reading and Literacy Development","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reading (process); Linguistics; Chinese characters; Psychology; Character (mathematics); Text segmentation; Punctuation; Kanji; Writing system; Computer science; Segmentation; Artificial intelligence; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002228532,0.0004864834,0.0004360955,0.000261594,0.0003489971,0.0004890574,0.0002514132,0.0005912675,0.004299394],"category_scores_gemma":[0.003453328,0.000403585,0.0002024104,0.0002311507,0.0004457469,0.0007708968,0.0007272716,0.0005983653,0.0004426581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002942981,"about_ca_system_score_gemma":0.0005459842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0065573,"about_ca_topic_score_gemma":0.01070632,"domain_scores_codex":[0.9997594,0.00003802776,0.00002733143,0.00008152065,0.00004793143,0.00004586997],"domain_scores_gemma":[0.9988752,0.0004696701,0.0002726105,0.00009113884,0.000131666,0.0001596816],"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":[0.00545325,0.0005374778,0.009509603,0.000407898,0.00003668747,0.0005332677,0.003130003,0.00003528513,0.964624,0.0001194608,0.0002775128,0.01533555],"study_design_scores_gemma":[0.0005465025,0.003256182,0.9049898,0.00009145718,0.0001422737,0.000538211,0.003651279,0.0007058839,0.08388052,0.0005963056,0.001543201,0.00005835089],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982496,0.000174078,0.0001028794,0.00003735818,0.00001045809,0.00002296455,0.00005733355,0.00001416815,0.001331087],"genre_scores_gemma":[0.997072,0.0003192428,0.0007683864,0.0001387109,0.000009034924,0.0001169028,0.0001639316,0.00003344451,0.001378361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0065573,"threshold_uncertainty_score":0.01438296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02430809436343485,"score_gpt":0.3518664182957326,"score_spread":0.3275583239322978,"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."}}