{"id":"W4414587284","doi":"10.48550/arxiv.2505.19848","title":"Improving Multilingual Math Reasoning for African Languages","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Mathematics Education and Teaching Techniques","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Languages of Africa; Adaptation (eye); Face (sociological concept); Work (physics); Base (topology); Selection (genetic algorithm)","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":[0.001797369,0.0009322047,0.0005423168,0.0005534577,0.0005700038,0.001528939,0.001235992,0.0007013592,0.006269513],"category_scores_gemma":[0.008271289,0.000340419,0.0008475819,0.0005573066,0.0004475018,0.003355773,0.002427999,0.002016194,0.002482463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008086986,"about_ca_system_score_gemma":0.001364958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004678033,"about_ca_topic_score_gemma":0.007382932,"domain_scores_codex":[0.9992612,0.0003968587,0.00003377123,0.0001862816,0.00007698338,0.00004491703],"domain_scores_gemma":[0.9973555,0.001892878,0.00008843826,0.0003509248,0.0002160309,0.00009631785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008627488,0.001159781,0.01383026,0.0009963682,0.0002495455,0.0004496272,0.002694225,0.2181069,0.01923082,0.01880964,0.01685979,0.7067503],"study_design_scores_gemma":[0.0001339805,0.0002173504,0.002599045,0.0001285199,0.00009412623,0.0001767672,0.0008435113,0.933163,0.01560588,0.02847714,0.01851761,0.00004307116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5296441,0.001785114,0.4175402,0.002394324,0.0002843714,0.0001943165,0.001689049,0.02321153,0.02325714],"genre_scores_gemma":[0.850955,0.0003807769,0.1408625,0.0003692799,0.00003244707,0.0001302097,0.002684851,0.0005235541,0.004061311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006269513,"threshold_uncertainty_score":0.02097362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06278846077736451,"score_gpt":0.4086311836720098,"score_spread":0.3458427228946453,"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."}}