{"id":"W6996506472","doi":"","title":"Semi-Supervised Named Entity Recognition:
\\nLearning to Recognize 100 Entity Types with Little Supervision
\\n","year":2007,"lang":"en","type":"dissertation","venue":"CogPrints (University of Southampton)","topic":"Mental Health Treatment and Access","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bibliothèque et Archives nationales du Québec","funders":"","keywords":"Named-entity recognition; Acronym; Task (project management); Hierarchy; Key (lock); Entity linking; Field (mathematics); Named entity; Listing (finance)","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":[0.002552518,0.001029473,0.0007188463,0.001341435,0.001088651,0.001826486,0.002602646,0.001207476,0.006872937],"category_scores_gemma":[0.007613456,0.00057407,0.001057303,0.001156982,0.001351577,0.004090216,0.002197261,0.001818103,0.006953564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007605731,"about_ca_system_score_gemma":0.001824425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002343634,"about_ca_topic_score_gemma":0.005208693,"domain_scores_codex":[0.9972367,0.0006690837,0.0002199532,0.001029514,0.0007374464,0.0001073451],"domain_scores_gemma":[0.9941897,0.001524401,0.0004535398,0.002421435,0.001306787,0.0001041676],"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":[0.0002124425,0.0002402312,0.004669716,0.0005733877,0.0001740617,0.0002770389,0.0006405432,0.01912729,0.07490581,0.04133077,0.05120558,0.8066431],"study_design_scores_gemma":[0.00004948351,0.0001616753,0.004457645,0.0002423117,0.0001025151,0.0009971489,0.0003565437,0.4900796,0.2511825,0.05423551,0.1979485,0.0001865403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008551268,0.0001779955,0.9762769,0.0003677619,0.0001593446,0.0001359177,0.0006470854,0.008220447,0.005463287],"genre_scores_gemma":[0.07617999,0.000278597,0.9073561,0.0005153161,0.00009589604,0.0002640474,0.004068076,0.0008952498,0.01034662],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006872937,"threshold_uncertainty_score":0.02299219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0322589000841657,"score_gpt":0.308060679264583,"score_spread":0.2758017791804173,"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."}}