{"id":"W6976775207","doi":"10.60692/rwdwm-ste41","title":"MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition","year":2022,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Named-entity recognition; Task (project management); Transfer of learning; Benchmark (surveying); Transfer (computing); Cover (algebra); Training set; Sequence labeling","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004589529,0.002305177,0.001137156,0.002438056,0.001284928,0.001782473,0.002897191,0.001617876,0.008176409],"category_scores_gemma":[0.006495256,0.0007390931,0.001503385,0.001557019,0.0004869811,0.004164523,0.004606307,0.002595765,0.006973213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000860407,"about_ca_system_score_gemma":0.001719012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006047606,"about_ca_topic_score_gemma":0.01179895,"domain_scores_codex":[0.9985244,0.0006142534,0.00008545979,0.0004338814,0.0001903313,0.0001517549],"domain_scores_gemma":[0.9985403,0.0005800049,0.0000836354,0.0004828894,0.0002283075,0.00008481348],"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":[0.001587374,0.001067419,0.01088955,0.001297161,0.001135925,0.0008845027,0.001280923,0.05764463,0.02155802,0.01080706,0.1933499,0.6984976],"study_design_scores_gemma":[0.0003711441,0.000683351,0.008859975,0.0002448982,0.0003163391,0.001279168,0.0008385449,0.7551333,0.05153035,0.0248074,0.1557137,0.0002218177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09970919,0.003899231,0.6484873,0.001619983,0.0009802385,0.00141338,0.02883902,0.2012193,0.01383229],"genre_scores_gemma":[0.3166783,0.001784686,0.5399263,0.00102866,0.0002612754,0.002205814,0.1105794,0.007325087,0.02021045],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008176409,"threshold_uncertainty_score":0.02735281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05388125223713194,"score_gpt":0.2027361766165257,"score_spread":0.1488549243793938,"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."}}