{"id":"W1586471131","doi":"","title":"A Readability Study and Its Relevance to Simplification on Translations of Lun Yu","year":2014,"lang":"en","type":"article","venue":"Studies in literature and language","topic":"Text Readability and Simplification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Readability; Sentence; Reading (process); Linguistics; Index (typography); Computer science; Relevance (law); Natural language processing; Philosophy; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.002976391,0.0003579466,0.0004049056,0.004009444,0.0008640169,0.001733508,0.0003667123,0.0002817844,0.003372778],"category_scores_gemma":[0.03124841,0.0001418584,0.000514317,0.003616702,0.001864324,0.003016739,0.0008683338,0.000641237,0.0002755157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001102509,"about_ca_system_score_gemma":0.0008358622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004222219,"about_ca_topic_score_gemma":0.002946451,"domain_scores_codex":[0.9967359,0.001608816,0.0003274226,0.0003283797,0.000877845,0.0001215883],"domain_scores_gemma":[0.9731631,0.01901317,0.002609539,0.001214842,0.003785056,0.0002142238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001441945,0.0005172612,0.3688163,0.001534727,0.0003277225,0.002987477,0.2267972,0.002333419,0.0238538,0.03085398,0.002343689,0.3381924],"study_design_scores_gemma":[0.00005453758,0.001124396,0.8870402,0.0002430387,0.0002226126,0.001105783,0.05740815,0.008027527,0.01723613,0.01585898,0.01157567,0.0001029619],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786177,0.0004904614,0.008408058,0.0003419012,0.00003075723,0.00010231,0.0001732309,0.0000360208,0.0117995],"genre_scores_gemma":[0.9964575,0.0001798865,0.002249233,0.00002429547,0.00001829614,0.0000608527,0.0001791309,0.00001678801,0.00081393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004222219,"threshold_uncertainty_score":0.01574081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0239070417033075,"score_gpt":0.3340671695770551,"score_spread":0.3101601278737476,"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."}}