{"id":"W4416047703","doi":"10.48550/arxiv.2505.21979","title":"Pearl: A Multimodal Culturally-Aware Arabic Instruction Dataset","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alliance de recherche numérique du Canada; Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Pearl; Benchmark (surveying); Arabic; Workflow; Benchmarking; Mainstream; Semantics (computer science)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002665317,0.000489799,0.0004345432,0.00025229,0.0003481515,0.0002910812,0.002925289,0.0003948559,0.00004538893],"category_scores_gemma":[0.0001714693,0.0004714876,0.0001808239,0.0004997589,0.00009543804,0.0004176807,0.00373329,0.001690243,0.0005864525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001945035,"about_ca_system_score_gemma":0.0002852857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004649038,"about_ca_topic_score_gemma":0.0001022066,"domain_scores_codex":[0.9969131,0.0002029593,0.0005356118,0.001505738,0.0003958018,0.0004467834],"domain_scores_gemma":[0.996411,0.0001159444,0.0003801141,0.002707926,0.0002137525,0.0001712334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000539399,0.0007938454,0.7898315,0.001164156,0.0005699423,0.00006874176,0.004090763,0.04745862,0.001631633,0.01104022,0.02578271,0.117514],"study_design_scores_gemma":[0.00076389,0.00003481818,0.7233551,0.0002431984,0.0000623728,0.00002524884,0.00004675067,0.2546228,0.0002469411,0.00109101,0.01862622,0.0008816005],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8398669,0.0001339271,0.1481492,0.005340742,0.00174291,0.001104138,0.001375842,0.001248501,0.00103788],"genre_scores_gemma":[0.9603963,0.00003941221,0.03391775,0.0005568301,0.0003041625,0.0003274729,0.003794566,0.00002453796,0.0006389773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2071642,"threshold_uncertainty_score":0.9997737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03124253345628599,"score_gpt":0.3130544899995196,"score_spread":0.2818119565432336,"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."}}