{"id":"W4416541694","doi":"10.48550/arxiv.2504.11814","title":"ARWI: Arabic Write and Improve","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Text Readability and Simplification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; New York University Abu Dhabi","keywords":"Arabic; Grammar; Modern Standard Arabic; Profiling (computer programming); Arabic languages; Error analysis","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":[0.002470197,0.001494771,0.0005903536,0.001475404,0.0007100367,0.002152458,0.001371215,0.000718603,0.04215483],"category_scores_gemma":[0.01470368,0.0003540898,0.0004387456,0.0008702513,0.0004287421,0.003293266,0.004030328,0.001441879,0.04453139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002718727,"about_ca_system_score_gemma":0.0008440719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004239518,"about_ca_topic_score_gemma":0.0007874956,"domain_scores_codex":[0.9979994,0.0005642533,0.0001625037,0.0004148384,0.0007351816,0.0001238217],"domain_scores_gemma":[0.993186,0.002151588,0.0005341222,0.001731508,0.001736594,0.0006601759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005091357,0.0003113866,0.001506028,0.0006661649,0.00003063353,0.0003041213,0.0025838,0.0007396395,0.02431174,0.00366677,0.2219742,0.7433965],"study_design_scores_gemma":[0.0002170034,0.0006536908,0.005548193,0.0003015703,0.00004157943,0.001172762,0.001143727,0.01452599,0.05026224,0.009060809,0.9169003,0.0001720493],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.05999884,0.00187247,0.3584176,0.002341933,0.0011579,0.001284114,0.01084849,0.4680607,0.09601803],"genre_scores_gemma":[0.1723694,0.00178295,0.5603375,0.001423744,0.000611511,0.002141146,0.02837546,0.04176005,0.1911981],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.04215483,"threshold_uncertainty_score":0.1410219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03535004254881862,"score_gpt":0.2728030644487988,"score_spread":0.2374530218999802,"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."}}