{"id":"W1518466950","doi":"10.1007/11557067_6","title":"A Lookahead Branch-and-Bound Algorithm for the Maximum Quartet Consistency Problem","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Heuristics; Branch and bound; Consistency (knowledge bases); Set (abstract data type); Algorithm; Heuristic; Construct (python library); Computer science; Scheme (mathematics); Running time; Upper and lower bounds; Mathematics; Mathematical optimization; Artificial intelligence","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":[0.002408969,0.001570591,0.002697546,0.001839719,0.001650534,0.002679277,0.004558727,0.002215924,0.02238127],"category_scores_gemma":[0.01047318,0.001259371,0.001722926,0.003865652,0.0012009,0.005194494,0.003548455,0.004373264,0.002721969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001493518,"about_ca_system_score_gemma":0.003510948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004045226,"about_ca_topic_score_gemma":0.007189216,"domain_scores_codex":[0.998394,0.0003789398,0.0001148343,0.0004427885,0.0004117672,0.0002576285],"domain_scores_gemma":[0.994184,0.003759468,0.0002607591,0.001025028,0.000502811,0.0002679782],"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":[0.001546495,0.0009529622,0.001325185,0.0007572475,0.0001691311,0.0001955328,0.0003390629,0.1687817,0.006466937,0.05943367,0.0412131,0.7188191],"study_design_scores_gemma":[0.0006037181,0.000211777,0.000437626,0.0000644368,0.0001201354,0.0001302926,0.0001250107,0.8138145,0.002568429,0.1774719,0.004413963,0.00003816443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02541294,0.0007564644,0.9580514,0.001228322,0.0003047117,0.0004032675,0.0006402105,0.00453261,0.008670052],"genre_scores_gemma":[0.1299779,0.0002889396,0.8609096,0.0005056575,0.0001703166,0.0004230914,0.001818163,0.001036464,0.004869945],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02238127,"threshold_uncertainty_score":0.07487285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01864115444346768,"score_gpt":0.2553862308276432,"score_spread":0.2367450763841755,"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."}}