{"id":"W2166470254","doi":"10.1145/1963192.1963217","title":"CELF++","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":857,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Heuristics; Computer science; Maximization; Greedy algorithm; Simple (philosophy); Node (physics); Set (abstract data type); Mathematical optimization; Monte Carlo method; Quadratic equation; Algorithm; Mathematics","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":[0.0009047828,0.001768497,0.001050428,0.001483215,0.001157576,0.002305102,0.004229539,0.001398349,0.06399979],"category_scores_gemma":[0.004268135,0.0006724781,0.001272904,0.0016164,0.0006635816,0.003201952,0.003069949,0.001586386,0.0419457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001740712,"about_ca_system_score_gemma":0.001821439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005917178,"about_ca_topic_score_gemma":0.007207975,"domain_scores_codex":[0.9987896,0.0001640753,0.00006171764,0.0003444664,0.0003570606,0.0002830722],"domain_scores_gemma":[0.9980925,0.0005109937,0.00007868289,0.0007346565,0.0004670195,0.000116241],"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":[0.001403927,0.0004684755,0.001498841,0.0007004419,0.00006641584,0.0002778346,0.0001194998,0.02631439,0.006850914,0.03463017,0.3410054,0.5866636],"study_design_scores_gemma":[0.0009380186,0.00045445,0.0008661406,0.0001266411,0.00006541675,0.001240687,0.00009939064,0.2686917,0.01847556,0.05147297,0.6574373,0.0001318157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02068347,0.001620897,0.6339163,0.002228702,0.001010874,0.001222388,0.01725266,0.2103424,0.1117224],"genre_scores_gemma":[0.113694,0.0006425483,0.7771363,0.002090118,0.000252592,0.001148415,0.03057355,0.01361451,0.060848],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06399979,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04872163073464558,"score_gpt":0.1971299117888966,"score_spread":0.148408281054251,"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."}}