{"id":"W4415526236","doi":"10.1007/978-3-032-01823-6_1","title":"TIRE: Advancing Threat Intelligence Relation Extraction with a Novel Data-Centric Framework","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Relationship extraction; Pipeline (software); Relation (database); Adaptability; Representation (politics); Information extraction; Sentence; Key (lock)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002418558,0.002224209,0.001969554,0.008625931,0.00138345,0.005321271,0.00331918,0.001715471,0.005476053],"category_scores_gemma":[0.00844716,0.0009381723,0.003115986,0.005915612,0.001064494,0.008072198,0.005559702,0.003238259,0.00619668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001080245,"about_ca_system_score_gemma":0.002613157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004304919,"about_ca_topic_score_gemma":0.01009801,"domain_scores_codex":[0.9963721,0.0003957305,0.0003081912,0.001028953,0.00171214,0.000182799],"domain_scores_gemma":[0.9962046,0.001371811,0.000316648,0.001185097,0.0007781445,0.0001438345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000225727,0.0005021148,0.005789061,0.00134286,0.0004017477,0.0004670543,0.0004576445,0.01123709,0.01725746,0.05504106,0.08477378,0.8225044],"study_design_scores_gemma":[0.00008872294,0.0002990066,0.004405801,0.0005422597,0.0005399328,0.001774185,0.0005531713,0.5496392,0.03633888,0.1857051,0.2199553,0.0001584222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00412111,0.001742846,0.9538507,0.0008470279,0.0002055856,0.0004577888,0.005840296,0.02892679,0.004007857],"genre_scores_gemma":[0.03663308,0.000950062,0.9397313,0.0006948568,0.0001938839,0.0003084276,0.01657691,0.0008778801,0.00403367],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008625931,"threshold_uncertainty_score":0.01831925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02257965097039168,"score_gpt":0.2960853008654644,"score_spread":0.2735056498950727,"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."}}