{"id":"W2808847742","doi":"10.1145/3219819.3220021","title":"Ranking Distillation","year":2018,"lang":"en","type":"article","venue":"","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":165,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Ranking (information retrieval); Computer science; Rank (graph theory); Inference; Distillation; Learning to rank; Machine learning; Artificial intelligence; Ranking SVM; Information retrieval; Mathematics","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":[0.002713491,0.001520846,0.001882309,0.001539389,0.0008072559,0.001704215,0.003346172,0.001671028,0.006893113],"category_scores_gemma":[0.01226759,0.0008105175,0.001256892,0.001793601,0.001060006,0.005011863,0.00229994,0.003347158,0.003747133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001050965,"about_ca_system_score_gemma":0.002106094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004463258,"about_ca_topic_score_gemma":0.00906688,"domain_scores_codex":[0.9970555,0.001072839,0.0001714684,0.0008485633,0.0006169248,0.0002347111],"domain_scores_gemma":[0.9948094,0.002070882,0.0003080507,0.001692499,0.000929205,0.0001900037],"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":[0.0003977259,0.0005179899,0.003260564,0.0004332285,0.0002266873,0.0001425317,0.0001656286,0.2796817,0.006689691,0.04869591,0.01960986,0.6401784],"study_design_scores_gemma":[0.00004038216,0.0001262108,0.0002778353,0.00001958391,0.000023897,0.00007002288,0.00001935192,0.9672989,0.004131288,0.02329292,0.004669059,0.00003053702],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01512518,0.000524174,0.9763054,0.0004919359,0.0001444367,0.0001003972,0.000428071,0.004163378,0.002717013],"genre_scores_gemma":[0.3980388,0.0004549592,0.5843645,0.0008155737,0.0002920062,0.000316654,0.003144254,0.0007277823,0.01184537],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006893113,"threshold_uncertainty_score":0.02305979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01447885775144485,"score_gpt":0.2501679671432046,"score_spread":0.2356891093917597,"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."}}