{"id":"W2180616177","doi":"10.1016/j.jda.2011.12.017","title":"Skip lift: A probabilistic alternative to red–black trees","year":2011,"lang":"en","type":"article","venue":"Journal of Discrete Algorithms","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Lift (data mining); Pointer (user interface); Computer science; Data structure; Combinatorics; Probabilistic logic; Algorithm; Mathematics; Discrete mathematics; Data mining; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002605244,0.0007586183,0.001586283,0.001618571,0.001469528,0.001819125,0.002391105,0.001523912,0.008731791],"category_scores_gemma":[0.01114937,0.0006401544,0.001140334,0.002291529,0.001437827,0.003946329,0.005092461,0.003031028,0.002006842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006257094,"about_ca_system_score_gemma":0.001625403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00155347,"about_ca_topic_score_gemma":0.002687845,"domain_scores_codex":[0.9981753,0.0004925533,0.00008011556,0.0002558842,0.0007626073,0.0002336441],"domain_scores_gemma":[0.9952446,0.001713627,0.0002059209,0.001872052,0.0006210308,0.0003427656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00131469,0.0002457925,0.001429176,0.0002057524,0.0001057315,0.0002565711,0.00029143,0.119503,0.006044331,0.4121089,0.02045134,0.4380433],"study_design_scores_gemma":[0.00007663746,0.0001059361,0.0003030258,0.00004364468,0.00004515151,0.0001662225,0.00004176282,0.5828242,0.002293156,0.4046985,0.009363947,0.00003780152],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0120779,0.0003093999,0.9817573,0.0003818266,0.0001765605,0.0000572809,0.0002080468,0.001274757,0.003756831],"genre_scores_gemma":[0.366119,0.0006817306,0.6166944,0.0008167792,0.0006282889,0.0002517553,0.0009374874,0.00139937,0.01247125],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008731791,"threshold_uncertainty_score":0.02921075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03582305399091825,"score_gpt":0.2703334173377777,"score_spread":0.2345103633468594,"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."}}