{"id":"W4390575962","doi":"10.1137/1.9781611977912.42","title":"Sorting and Selection in Rounds with Adversarial Comparisons","year":2024,"lang":"en","type":"book-chapter","venue":"Society for Industrial and Applied Mathematics eBooks","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Sorting; Selection (genetic algorithm); Upper and lower bounds; Combinatorics; Constant (computer programming); Sorting algorithm; Binary logarithm; Mathematics; Sorting network; Computer science; Selection algorithm; Deterministic algorithm; Randomized algorithm; Algorithm; Discrete mathematics; Artificial intelligence","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":[0.004336146,0.001124176,0.001054704,0.001202341,0.001461626,0.004627919,0.002256794,0.002372665,0.01466258],"category_scores_gemma":[0.01678171,0.0005289942,0.001524041,0.001841872,0.004564947,0.01024909,0.003653,0.005227822,0.003677766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003153609,"about_ca_system_score_gemma":0.001482142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006449856,"about_ca_topic_score_gemma":0.0006170174,"domain_scores_codex":[0.9953904,0.001997046,0.0001964732,0.0007073097,0.001318877,0.0003898259],"domain_scores_gemma":[0.9911765,0.005984012,0.0005325227,0.001721083,0.0004022624,0.0001837401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006492079,0.00001823754,0.0000921555,0.00005726836,0.00001385953,0.00004687169,0.00006964831,0.01692049,0.0006247806,0.9527636,0.004709436,0.02461871],"study_design_scores_gemma":[0.00001175967,0.00004788439,0.00006841771,0.00004261368,0.000009585934,0.00008485053,0.00003301042,0.05187707,0.001125255,0.9295222,0.01715858,0.00001876976],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01544581,0.001634205,0.7968308,0.004914612,0.0008984167,0.0002263107,0.0002757924,0.0006718683,0.1791023],"genre_scores_gemma":[0.5207467,0.003425643,0.3111002,0.002937794,0.001422708,0.00068891,0.0004251586,0.0008447922,0.1584082],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01466258,"threshold_uncertainty_score":0.04905128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0408580626423147,"score_gpt":0.2511247736164804,"score_spread":0.2102667109741657,"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."}}