{"id":"W4411399482","doi":"10.1016/j.knosys.2025.113914","title":"Task-Oriented Dynamic Knowledge Distillation for Continuous Few-Shot Relation Extraction","year":2025,"lang":"en","type":"article","venue":"Knowledge-Based Systems","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Key Laboratory of Software Engineering of Yunnan Province; Yunnan Provincial Department of Education; Yunnan University; Natural Science Foundation of Yunnan Province","keywords":"Distillation; Shot (pellet); Relation (database); Extraction (chemistry); Task (project management); Computer science; One shot; Process engineering; Chromatography; Chemistry; Engineering; Data mining; Mechanical engineering; Systems engineering; Organic 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001428897,0.001607229,0.002055088,0.002401549,0.001101911,0.001742197,0.003484164,0.002259657,0.004912305],"category_scores_gemma":[0.005637031,0.0007311204,0.001356304,0.002537045,0.0007867233,0.004077532,0.003629304,0.002934243,0.002789408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006983608,"about_ca_system_score_gemma":0.001764884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00660993,"about_ca_topic_score_gemma":0.01131609,"domain_scores_codex":[0.9987888,0.0001990616,0.00008568075,0.0005723509,0.0002245128,0.0001295524],"domain_scores_gemma":[0.9975458,0.00131763,0.0001140716,0.0005583626,0.0003376987,0.0001263932],"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":[0.0004852899,0.0004872973,0.0008215939,0.0004413113,0.0001864083,0.0002974566,0.0002284563,0.03666374,0.03663575,0.004831558,0.01414011,0.904781],"study_design_scores_gemma":[0.00002394389,0.00008073277,0.0007102617,0.00003858628,0.00007295698,0.0001836027,0.00009833374,0.9605715,0.01835711,0.01549168,0.004331447,0.00003992752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02118584,0.001355948,0.9671988,0.0003083563,0.0001764745,0.0001386459,0.0009327089,0.006981428,0.001721866],"genre_scores_gemma":[0.3967806,0.0009917635,0.5880668,0.0005836937,0.0002491714,0.00028982,0.006171164,0.0007026811,0.006164302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00660993,"threshold_uncertainty_score":0.01643336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01926814035735111,"score_gpt":0.3110560843494454,"score_spread":0.2917879439920943,"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."}}