{"id":"W2062257519","doi":"","title":"Approximation algorithms for labeling hierarchical taxonomies","year":2008,"lang":"en","type":"article","venue":"CaltechAUTHORS (California Institute of Technology)","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Linear programming relaxation; Approximation algorithm; Extension (predicate logic); Mathematics; Algorithm; Linear programming; Steiner tree problem; Discrete mathematics; Combinatorics; Relaxation (psychology); Computer science","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":[0.002740147,0.001697076,0.001815918,0.001943999,0.001367016,0.002665722,0.003818753,0.002292639,0.008029241],"category_scores_gemma":[0.009931512,0.001029164,0.00170878,0.005797418,0.00101738,0.00714694,0.002227746,0.00277497,0.001392176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004085778,"about_ca_system_score_gemma":0.002688291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008329226,"about_ca_topic_score_gemma":0.01533177,"domain_scores_codex":[0.9978109,0.0006243697,0.0001302689,0.0005410523,0.0004938106,0.0003996922],"domain_scores_gemma":[0.995545,0.002785256,0.0003911609,0.0008026767,0.0002442081,0.0002315846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005613986,0.0006324212,0.002536005,0.0007821076,0.000148086,0.0001253722,0.0005798173,0.6192946,0.002287232,0.08267996,0.0219798,0.2683931],"study_design_scores_gemma":[0.0000988517,0.00005722511,0.0003089919,0.00004520192,0.00003781945,0.00008106619,0.0001265953,0.919741,0.000576158,0.07554027,0.003373501,0.00001331353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05734639,0.001485687,0.9269434,0.00145385,0.0001078825,0.000334211,0.001488362,0.002435457,0.008404786],"genre_scores_gemma":[0.1871182,0.0008872242,0.8032442,0.0003609257,0.000104901,0.0004864143,0.003613658,0.000370191,0.003814229],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008329226,"threshold_uncertainty_score":0.02964455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0422268616914309,"score_gpt":0.2626705395891018,"score_spread":0.2204436778976709,"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."}}