{"id":"W1897679864","doi":"10.5555/1496770.1496787","title":"Comparison-based time-space lower bounds for selection","year":2009,"lang":"en","type":"article","venue":"","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Upper and lower bounds; Binary logarithm; Combinatorics; Log-log plot; Mathematics; Mathematical proof; Streaming algorithm; Space (punctuation); Selection (genetic algorithm); Discrete mathematics; Running time; Randomized algorithm; Computer science; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001714809,0.0001059991,0.0001393383,0.00009294401,0.0002124524,0.000198544,0.0004304145,0.00004546099,0.00007247357],"category_scores_gemma":[0.000017775,0.00009923599,0.00009745751,0.0004153753,0.00002539581,0.0002115779,0.00002448766,0.0000784705,0.00005877391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000029401,"about_ca_system_score_gemma":0.00006299529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008170956,"about_ca_topic_score_gemma":0.000008046848,"domain_scores_codex":[0.9991493,0.0000198046,0.0001452215,0.0002783231,0.0001613068,0.0002460658],"domain_scores_gemma":[0.9994323,0.0001056899,0.00004499495,0.0002612919,0.00008972366,0.00006596293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000745554,0.001137337,0.0006763438,0.00001728348,0.00003056402,0.000002909564,0.0002358444,0.003983206,0.00392318,0.6307655,0.1952548,0.1638985],"study_design_scores_gemma":[0.0003315396,0.0004433187,0.0007707028,0.000005499199,0.00000324112,0.000001987873,0.000002301406,0.926923,0.005033012,0.01947186,0.04685397,0.0001595985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001317417,0.00002339025,0.9877049,0.003650986,0.0002581162,0.000166427,0.00000104954,0.0003781392,0.006499581],"genre_scores_gemma":[0.5192745,4.971772e-7,0.4767155,0.001629236,0.0001071954,0.00001068389,0.000004103173,0.000004959273,0.002253356],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9229398,"threshold_uncertainty_score":0.4046727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02316411013063129,"score_gpt":0.2960447433243519,"score_spread":0.2728806331937206,"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."}}