{"id":"W7077857648","doi":"10.48448/yhst-2q50","title":"Efficient Document-level Event Relation Extraction","year":2025,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Event (particle physics); Relation (database); Pairwise comparison; Coreference; Event data; Relationship extraction","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":[],"consensus_categories":[],"category_scores_codex":[0.0008560766,0.0002453648,0.0001972097,0.0005033036,0.0002791129,0.0002086258,0.001435535,0.0002134047,0.0004753129],"category_scores_gemma":[0.0002659624,0.0002251701,0.00006120754,0.001139876,0.0002520277,0.0001383789,0.0005141494,0.0003002666,0.0002153935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001931803,"about_ca_system_score_gemma":0.0006933833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001334679,"about_ca_topic_score_gemma":0.00002434803,"domain_scores_codex":[0.9976241,0.00003904575,0.0003034628,0.0008854161,0.0007138009,0.0004341636],"domain_scores_gemma":[0.9984862,0.00006240571,0.0003066764,0.0008521262,0.0001801314,0.0001124274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007988463,0.0004595855,0.0001646695,0.0002900997,0.00007391075,0.00005680278,0.0003993824,0.04436768,0.005284185,0.497975,0.2777779,0.1731428],"study_design_scores_gemma":[0.0003616723,0.00005062738,0.0005658559,0.0004050792,0.00002328957,0.00002754596,0.00005287907,0.3297241,0.001802085,0.01317285,0.6531799,0.0006341187],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00001210546,0.0001123327,0.4803838,0.001734224,0.001069333,0.0001829785,0.000004445418,0.0002738144,0.5162269],"genre_scores_gemma":[0.05395373,0.00002570502,0.05305865,0.0002375004,0.0002063278,0.00001904115,0.0000203644,0.00001716609,0.8924615],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4848021,"threshold_uncertainty_score":0.9182172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01894739660936215,"score_gpt":0.2859083759684464,"score_spread":0.2669609793590843,"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."}}