{"id":"W2807391974","doi":"","title":"TCS Research at TAC 2017: Joint Extraction of Entities and Relations from Drug Labels using an Ensemble of Neural Networks.","year":2017,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial neural network; Joint (building); Extraction (chemistry); Artificial intelligence; Machine learning; Chemistry; Chromatography; 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":[0.0005154179,0.00005879065,0.0001263333,0.00003330947,0.0003347949,0.00001605008,0.0001183247,0.00008849418,0.000009035402],"category_scores_gemma":[0.0001118978,0.00005248224,0.00002116159,0.00003155223,0.001253238,0.00001351069,0.0001339932,0.00006641253,2.055845e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003328034,"about_ca_system_score_gemma":0.00002127939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001944096,"about_ca_topic_score_gemma":0.00005867062,"domain_scores_codex":[0.9994177,0.0001039516,0.0001708998,0.0001456811,0.00007437816,0.00008741675],"domain_scores_gemma":[0.9991945,0.0001122767,0.0001785282,0.0003597642,0.0001208297,0.0000340795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002637542,0.0001418564,0.005299401,0.00007896475,0.00008101675,3.417036e-7,0.0009536311,0.0001553286,0.9003953,0.06522082,0.0003909397,0.02701862],"study_design_scores_gemma":[0.0006391894,0.0003051138,0.02888622,0.00005574458,0.0001149035,0.0000138857,0.00522901,0.001478402,0.811316,0.1456892,0.006020962,0.0002514153],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868329,0.003279473,0.009295033,0.00007396057,0.00002514093,0.00009854836,0.00003669333,0.000004213147,0.00035403],"genre_scores_gemma":[0.9980169,0.0005336492,0.0008853643,0.000003560672,0.00006457671,0.00001509501,0.0000500518,0.000005041677,0.0004257914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08907937,"threshold_uncertainty_score":0.4617606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05898442574939388,"score_gpt":0.3593710565403336,"score_spread":0.3003866307909397,"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."}}