{"id":"W2145677964","doi":"","title":"A Genetic Algorithm for the Minimum Tetrahedralization of a Convex Polyhedron.","year":2003,"lang":"en","type":"article","venue":"Canadian Conference on Computational Geometry","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Polyhedron; Regular polygon; Convex polytope; Tetrahedron; Partition (number theory); Combinatorics; Mathematics; Algorithm; Mathematical optimization; Computer science; Convex set; Convex optimization; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003371779,0.0001838474,0.0001939769,0.0005874856,0.0003083747,0.0001520083,0.0005426913,0.00008560322,0.000111949],"category_scores_gemma":[0.0002080199,0.0001649476,0.00009999934,0.00114304,0.00008872232,0.0001705947,0.00002212692,0.0001040614,0.00002762435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001090289,"about_ca_system_score_gemma":0.001704328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000593545,"about_ca_topic_score_gemma":0.0005331222,"domain_scores_codex":[0.9984071,0.00009021469,0.0003718752,0.000393015,0.0004025997,0.0003352121],"domain_scores_gemma":[0.9978896,0.0007261823,0.0001598878,0.0003119867,0.0006692489,0.0002431373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004212185,0.00005278459,0.0001815118,0.00001697108,0.0000596223,0.00000381245,0.0001680388,0.1149703,0.00004150378,0.7207063,0.001890594,0.1619043],"study_design_scores_gemma":[0.0005546192,0.0001736372,0.006754521,0.0000207509,0.00001482713,0.00002690135,0.00005579989,0.942519,0.0002922043,0.04002221,0.00932881,0.0002367207],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003245329,0.000284272,0.9929087,0.001184648,0.0006309497,0.0004742866,0.00007525399,0.00003079606,0.001165826],"genre_scores_gemma":[0.8421531,0.00001188415,0.1562429,0.001096563,0.00007782014,0.00005780392,0.00005106122,0.00001190221,0.000297033],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8389077,"threshold_uncertainty_score":0.6726367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0257945182085321,"score_gpt":0.2495050461420711,"score_spread":0.223710527933539,"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."}}