{"id":"W4206308010","doi":"10.1137/1.9781611977073.78","title":"Selectable Heaps and Optimal Lazy Search Trees","year":2022,"lang":"en","type":"book-chapter","venue":"Society for Industrial and Applied Mathematics eBooks","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Heap (data structure); Priority queue; Amortized analysis; Merge (version control); Combinatorics; Queue; Binary logarithm; Binary search tree; Data structure; Mathematics; Time complexity; Computer science; Discrete mathematics; Parallel computing; Algorithm; Binary tree; Programming language","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004818834,0.000353358,0.0005118576,0.00004448359,0.0006262418,0.0002746317,0.0004798734,0.0004174217,0.00004197489],"category_scores_gemma":[0.000005214271,0.0003118332,0.0002108896,0.00002527732,0.0001412175,0.00008101931,0.001130273,0.00066974,0.000002399333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004606088,"about_ca_system_score_gemma":0.0001579398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007084806,"about_ca_topic_score_gemma":9.195812e-7,"domain_scores_codex":[0.998313,0.000005055026,0.0003539509,0.0005799558,0.0003971783,0.0003508357],"domain_scores_gemma":[0.9989796,0.0002408784,0.00018363,0.0004092926,0.00004043293,0.0001461953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000143105,0.0000224,7.35658e-8,0.0001288511,0.0001232619,0.000001078444,0.001289536,0.00001089115,0.0001546994,0.9383656,0.01181924,0.04807001],"study_design_scores_gemma":[0.002892028,0.0004150371,1.718182e-7,0.0002036715,0.0001891266,0.00004291391,0.0004675316,0.02375992,0.0007980855,0.1989441,0.7711663,0.001121149],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.000971169,0.001080955,0.2339161,0.0005721319,0.0008195788,0.005930525,0.001216325,0.000672649,0.7548206],"genre_scores_gemma":[0.0006264535,0.0003352777,0.6182269,0.0003650958,0.001586601,0.0004734563,0.0002875578,0.0002083353,0.3778903],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.759347,"threshold_uncertainty_score":0.9999334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05916056070832934,"score_gpt":0.24760370635386,"score_spread":0.1884431456455307,"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."}}