{"id":"W2404631988","doi":"","title":"WebTLab: A cooccurrence-based approach to KBP 2010 Entity-Linking task.","year":2010,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Intuition; Computer science; Task (project management); Information retrieval; Knowledge base; Artificial intelligence; Machine learning; Data mining; Cognitive science; Engineering","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":[0.0006063193,0.0001093943,0.0001583838,0.000107062,0.0001985369,0.00009929319,0.0007454932,0.00006413255,0.000006744155],"category_scores_gemma":[0.00006328235,0.00009373668,0.00003331096,0.0003618177,0.0002956814,0.000181177,0.0001525978,0.0001485461,0.00001730236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003273928,"about_ca_system_score_gemma":0.00007150889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001915389,"about_ca_topic_score_gemma":0.00001037502,"domain_scores_codex":[0.9992024,0.00004606172,0.0001790272,0.0002829681,0.0001254146,0.0001641378],"domain_scores_gemma":[0.9988369,0.0002697309,0.0000825839,0.0006342677,0.0001054577,0.00007105911],"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":[0.000009043889,0.00007150937,0.0004197019,0.00003147417,0.000005761718,1.112048e-7,0.0004615572,0.00001538422,0.003575559,0.9727575,0.0001079684,0.02254449],"study_design_scores_gemma":[0.0003773295,0.00007233928,0.003624615,0.00001661996,0.00003308341,0.00001284139,0.0006145228,0.001690348,0.04011485,0.9150606,0.03798396,0.0003988487],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04112384,0.0001527614,0.9528746,0.000323592,0.0001429713,0.000286701,0.00000681898,0.0001224261,0.004966259],"genre_scores_gemma":[0.9669961,0.000007953846,0.03244952,0.0001389461,0.00005749795,0.0001748613,0.000008227896,0.000004419521,0.0001625092],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9258722,"threshold_uncertainty_score":0.3822471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01283418924114096,"score_gpt":0.2486989356056279,"score_spread":0.235864746364487,"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."}}