{"id":"W7002330511","doi":"","title":"Named entity recognition for African languages : a focus on the Igbo language","year":2025,"lang":"en","type":"other","venue":"Lancaster EPrints (Lancaster University)","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Atomic Energy of Canada Limited","keywords":"Igbo; Named-entity recognition; Focus (optics); Languages of Africa; Task (project management); Style (visual arts); Information extraction; Projection (relational algebra); First language","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":[0.00199473,0.000732592,0.0006362552,0.001582179,0.001487958,0.001726106,0.0008110323,0.0005974139,0.004772218],"category_scores_gemma":[0.005465437,0.0003600689,0.0007437507,0.002126032,0.001301332,0.00626161,0.0030408,0.001889731,0.002361854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001078717,"about_ca_system_score_gemma":0.00207563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01178323,"about_ca_topic_score_gemma":0.01380333,"domain_scores_codex":[0.9991223,0.0003716752,0.00004782192,0.0002226297,0.000131808,0.0001036382],"domain_scores_gemma":[0.9984307,0.0007546056,0.000090581,0.0003137693,0.0003396398,0.00007064299],"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":[0.0009303141,0.0003120385,0.02189425,0.002944312,0.0001491819,0.002828181,0.01091114,0.01698465,0.04524293,0.1299351,0.05758274,0.7102851],"study_design_scores_gemma":[0.0001032783,0.0002567805,0.03080095,0.002253352,0.0001516228,0.003069395,0.008912358,0.08219395,0.04684911,0.04447383,0.78071,0.0002254679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4560488,0.01627417,0.3601772,0.0148325,0.001778417,0.0009377429,0.01051706,0.005241335,0.1341928],"genre_scores_gemma":[0.7217628,0.01230772,0.2131051,0.002748305,0.0004281564,0.0009377535,0.02217165,0.002460602,0.02407788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01178323,"threshold_uncertainty_score":0.02342933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01617489049147094,"score_gpt":0.2283276672579858,"score_spread":0.2121527767665149,"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."}}