{"id":"W2220328383","doi":"10.1145/3053370","title":"Array Layouts for Comparison-Based Searching","year":2017,"lang":"en","type":"article","venue":"ACM Journal of Experimental Algorithmics","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Cache; Binary search algorithm; Value (mathematics); Parallel computing; Binary tree; Binary number; Latency (audio); Algorithm; Search algorithm; Arithmetic; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005278689,0.0001254811,0.0002457997,0.0001067422,0.0005238156,0.0004771859,0.002625963,0.00004831731,0.000002324192],"category_scores_gemma":[0.0002192325,0.0001124728,0.0001507365,0.00004411058,0.00006628147,0.000526124,0.0002498037,0.0001749603,0.000001898173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006547713,"about_ca_system_score_gemma":0.0001226058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007891732,"about_ca_topic_score_gemma":3.068111e-7,"domain_scores_codex":[0.9989034,0.00004214227,0.0003859467,0.0001633775,0.0002875501,0.0002175732],"domain_scores_gemma":[0.9981833,0.0001507672,0.0006439362,0.0006991875,0.0002042953,0.0001185036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001180216,0.006611218,0.02200836,0.0001647499,0.0009567592,0.0003449321,0.01707782,0.09024719,0.2815409,0.04270793,0.06761763,0.4695423],"study_design_scores_gemma":[0.001307338,0.0008311906,0.0003153943,0.0000787841,0.00000702594,0.00004692767,0.00009627295,0.5049585,0.4879531,0.002074581,0.002092018,0.0002388469],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009824527,0.0003589927,0.987875,0.0008684288,0.0005699006,0.000110855,0.000002113283,0.00005538807,0.0003347252],"genre_scores_gemma":[0.4610984,0.000005102595,0.5386302,0.000114009,0.0001298308,0.00000241661,7.39235e-7,0.000006738388,0.0000125591],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4693035,"threshold_uncertainty_score":0.4879736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05509203364200714,"score_gpt":0.3722407228452136,"score_spread":0.3171486892032064,"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."}}