{"id":"W2059854631","doi":"10.1007/s11145-005-3356-y","title":"Differential Reading, Naming, and Transcribing Speeds of Japanese Romaji and Hiragana","year":2005,"lang":"en","type":"article","venue":"Reading and Writing","topic":"EFL/ESL Teaching and Learning","field":"Arts and Humanities","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Kanji; Writing system; Syllabic verse; Reading (process); Linguistics; Psychology; Chinese characters; Psycholinguistics; Computer science; Cognition; Speech recognition; Artificial intelligence","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":[0.0007682409,0.0004102569,0.0004866002,0.000809081,0.0006266165,0.0006904458,0.0003282649,0.0005768668,0.00441755],"category_scores_gemma":[0.004524712,0.0003822542,0.0003078739,0.0005043655,0.0005963137,0.0009892979,0.0004850113,0.0005638204,0.00091824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001896196,"about_ca_system_score_gemma":0.0002997915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007244775,"about_ca_topic_score_gemma":0.009804904,"domain_scores_codex":[0.9995869,0.00006444867,0.00006707145,0.0001505012,0.00006474111,0.00006635475],"domain_scores_gemma":[0.997343,0.00111218,0.0003871657,0.0002147954,0.000669628,0.000273284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0081572,0.0008706122,0.4205839,0.0005865958,0.0003218523,0.0060923,0.04320892,0.0005149281,0.4078815,0.0007627001,0.001556199,0.1094633],"study_design_scores_gemma":[0.00004932966,0.0005324388,0.9780091,0.00001595417,0.0001701619,0.001531735,0.005796573,0.0005762106,0.01189547,0.0003068572,0.001064333,0.0000517668],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987716,0.00009623924,0.0001424951,0.0000177142,0.00001064848,0.000006002518,0.00006389619,0.000005803542,0.0008856741],"genre_scores_gemma":[0.9974371,0.0001032318,0.0003446391,0.0000311912,0.000009296704,0.00001662553,0.0001843079,0.00001872224,0.001854811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007244775,"threshold_uncertainty_score":0.01477814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02498581772955092,"score_gpt":0.2442181908872779,"score_spread":0.219232373157727,"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."}}