{"id":"W4392011625","doi":"10.48550/arxiv.2402.11148","title":"Knowledge Distillation Based on Transformed Teacher Matching","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Educational Technology and Assessment","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Distillation; Matching (statistics); Process engineering; Computer science; Mathematics education; Chromatography; Mathematics; Chemistry; Engineering; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001365595,0.0009447914,0.00115177,0.0008704699,0.0006232695,0.001314459,0.002094502,0.001512894,0.005729415],"category_scores_gemma":[0.009270728,0.0003537811,0.0007411297,0.001361683,0.001001629,0.004354676,0.003528974,0.002519166,0.001690688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009160301,"about_ca_system_score_gemma":0.001829327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002793537,"about_ca_topic_score_gemma":0.00349139,"domain_scores_codex":[0.9986664,0.000333255,0.00008448567,0.0004851588,0.0003110452,0.0001196264],"domain_scores_gemma":[0.9981828,0.0007476563,0.0001881575,0.0004405035,0.0003123007,0.0001285401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003985978,0.0003717479,0.002587273,0.0003051184,0.0000838502,0.0001429059,0.0004086745,0.1869623,0.01487917,0.04095268,0.007480322,0.7454273],"study_design_scores_gemma":[0.00004167164,0.0001328147,0.0004590924,0.00002258236,0.00002233966,0.00008813653,0.00004973719,0.954434,0.01066103,0.03078887,0.003275305,0.00002451476],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03998518,0.0003583356,0.9526097,0.0005004964,0.0000970922,0.0001083734,0.0002633726,0.002853093,0.003224432],"genre_scores_gemma":[0.7207779,0.000233165,0.2686541,0.0003819188,0.00009457131,0.0002795969,0.0007655887,0.000325201,0.00848802],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005729415,"threshold_uncertainty_score":0.01916677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06581722171835075,"score_gpt":0.233751790873627,"score_spread":0.1679345691552762,"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."}}