{"id":"W2774310322","doi":"10.1109/iceca.2017.8203701","title":"Construction of estimated level based balanced binary search tree","year":2017,"lang":"en","type":"article","venue":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Tree traversal; Binary search tree; Binary tree; Computer science; Data structure; Tree (set theory); Binary number; Block (permutation group theory); Linked list; Memory management; Self-balancing binary search tree; Node (physics); Optimal binary search tree; Key (lock); Auxiliary memory; Tree structure; Algorithm; Interval tree; Mathematics; Arithmetic; Semiconductor memory; Computer hardware; Operating system; Engineering; Combinatorics","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":[0.000223791,0.0004284371,0.0007303095,0.001261125,0.0004953041,0.001155113,0.001096277,0.0006243738,0.007462918],"category_scores_gemma":[0.001481857,0.000380275,0.0004683982,0.001065155,0.0002570758,0.001251813,0.0009190982,0.000447703,0.002522155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005850644,"about_ca_system_score_gemma":0.001392961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002917592,"about_ca_topic_score_gemma":0.003788885,"domain_scores_codex":[0.99953,0.00004637459,0.00003447707,0.00009796289,0.0002063956,0.00008487705],"domain_scores_gemma":[0.9995255,0.00009408325,0.00004870234,0.00004080094,0.0002521715,0.00003874049],"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":[0.0006924771,0.00016182,0.006691475,0.0006829633,0.00008627601,0.001094814,0.0004051939,0.1735719,0.08685737,0.0387901,0.0269627,0.6640029],"study_design_scores_gemma":[0.0001164888,0.0002915416,0.001758093,0.00009132893,0.00008093186,0.001351175,0.0002598711,0.9100006,0.02552595,0.02305036,0.03740481,0.00006891444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02570442,0.0006518487,0.9634538,0.0002506183,0.00008320758,0.0001768315,0.0008623051,0.001501216,0.007315776],"genre_scores_gemma":[0.2692249,0.0006679982,0.715075,0.0001845053,0.00005961163,0.0003543927,0.003910929,0.0003086508,0.01021401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007462918,"threshold_uncertainty_score":0.02496594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09255252992105223,"score_gpt":0.3422129583233829,"score_spread":0.2496604284023307,"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."}}