{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005068076,0.0005196547,0.0007913379,0.0006906856,0.0006443605,0.00005347636,0.0006891501,0.0006454346,0.03646932],"category_scores_gemma":[0.00005221048,0.0005936062,0.0002634241,0.0007869001,0.000129173,0.0003185294,0.0001530823,0.0006999219,0.005247627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002109687,"about_ca_system_score_gemma":0.000131067,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009254103,"about_ca_topic_score_gemma":0.01572524,"domain_scores_codex":[0.9970324,0.000193443,0.0004298035,0.001059357,0.0006103101,0.0006746909],"domain_scores_gemma":[0.9977238,0.0001721472,0.0004771382,0.0006481357,0.0005276453,0.0004511232],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01295581,0.002785407,0.1575628,0.002228081,0.002022868,0.0006039037,0.08112296,0.00001005287,0.0005316358,0.00008827831,0.00627424,0.733814],"study_design_scores_gemma":[0.01113595,0.001571178,0.8207169,0.003665922,0.001522786,0.00003481693,0.1368993,0.00005364281,0.001578236,0.0004937153,0.01958404,0.002743538],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9351397,0.0002097644,0.0002696823,0.00008712519,0.001243525,0.001149285,0.0002473427,0.0001528052,0.06150084],"genre_scores_gemma":[0.9242362,0.0001165147,0.001130513,0.0001154969,0.0001504962,0.000009662264,0.003800999,0.00008373909,0.07035638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7310705,"threshold_uncertainty_score":0.9996516,"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."}}