{"id":"W2398614220","doi":"","title":"Overview of the TAC2013 Knowledge Base Population Evaluation: English Sentiment Slot Filling.","year":2013,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sentiment analysis; Variety (cybernetics); Polarity (international relations); Computer science; Task (project management); Knowledge base; Population; Base (topology); Entity linking; Track (disk drive); Natural language processing; Artificial intelligence; Information retrieval; Engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009166963,0.00007772851,0.0001347078,0.0000589405,0.0001401104,0.00004713993,0.0003325204,0.00002753592,0.0001696813],"category_scores_gemma":[0.00004392692,0.0000553495,0.00006345077,0.0003980995,0.00008835523,0.0002626718,0.0001368477,0.00003847301,0.000009465792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001071037,"about_ca_system_score_gemma":0.0000299961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002751357,"about_ca_topic_score_gemma":0.000002171802,"domain_scores_codex":[0.9991054,0.0001739026,0.0002786531,0.0001658804,0.0001915098,0.00008465738],"domain_scores_gemma":[0.9987329,0.0001707059,0.0002133368,0.0004795522,0.0003737607,0.00002970225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000001319591,0.0000495988,0.0009495791,0.00002943073,0.00002357143,2.818024e-9,0.001011488,0.00007673756,0.0003030394,0.9674563,0.0001604761,0.02993849],"study_design_scores_gemma":[0.0006425156,0.00005056527,0.04233171,0.0001011545,0.0002410659,0.000001313421,0.00211438,0.05187513,0.03424752,0.8606693,0.007378569,0.0003467672],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5999209,0.02118821,0.3525859,0.001100656,0.0006441573,0.003490906,0.00001796007,0.0001551662,0.02089603],"genre_scores_gemma":[0.998252,0.00008530843,0.001098894,0.00002567914,0.00005386368,0.0001636714,0.00001393793,0.000003454826,0.0003031539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3983311,"threshold_uncertainty_score":0.2257087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02827833491277492,"score_gpt":0.293756293748324,"score_spread":0.265477958835549,"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."}}