{"id":"W4241033854","doi":"10.1007/978-1-4939-7131-2_100333","title":"Entity Extraction","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Extraction (chemistry); Computer science; Chromatography; Chemistry","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002559843,0.0001410584,0.0002170172,0.0002219906,0.00008694269,0.0003628025,0.0007173812,0.0001568377,0.1794453],"category_scores_gemma":[0.0003339285,0.0001022966,0.0001374956,0.00003349266,0.000108027,0.0003779916,0.0003656,0.0001300425,0.07638179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003195017,"about_ca_system_score_gemma":0.00002389034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003199526,"about_ca_topic_score_gemma":0.0003956486,"domain_scores_codex":[0.9974689,0.0000277804,0.0004876065,0.0005143135,0.001388203,0.0001131419],"domain_scores_gemma":[0.9981816,0.0002467079,0.0002776248,0.001031266,0.0001973101,0.00006546831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003845573,0.000005036484,6.418809e-7,0.000001689325,0.00001000064,0.000002592703,0.00001335279,4.148107e-8,7.360694e-7,0.4101158,0.5547251,0.0351212],"study_design_scores_gemma":[0.00002527015,0.00001925911,0.00001785198,0.00000559306,0.000009709216,8.565578e-7,0.00002445268,0.000005263026,0.000005895135,0.3849719,0.6148322,0.00008163755],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000006758412,0.00002525382,0.02022748,0.0004328944,0.00125979,0.0001253925,0.00005009143,0.00005497184,0.9778174],"genre_scores_gemma":[0.0001678916,0.00004869834,0.0007209411,0.0007009143,0.0003469721,0.000001542643,0.00003963952,0.000009486822,0.9979639],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1030635,"threshold_uncertainty_score":0.9243374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3408290175831832,"score_gpt":0.4610012396116445,"score_spread":0.1201722220284613,"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."}}