{"id":"W2352553701","doi":"","title":"A Stationary Honeycomb Subdivision","year":2007,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subdivision; Computer science; Eigenvalues and eigenvectors; Circulant matrix; Mathematical optimization; Algorithm; Honeycomb; Matrix (chemical analysis); Mathematics; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001664387,0.0003118865,0.0004618286,0.000539249,0.000421462,0.0006581242,0.0008683794,0.0004700893,0.004389499],"category_scores_gemma":[0.0005325378,0.0001912407,0.0004780662,0.0005868812,0.0004911005,0.0006546351,0.0009227088,0.0005567741,0.001517534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002610534,"about_ca_system_score_gemma":0.0004904166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001320915,"about_ca_topic_score_gemma":0.001195865,"domain_scores_codex":[0.9997428,0.00003736556,0.00001239599,0.00004526047,0.0001346325,0.00002744655],"domain_scores_gemma":[0.9998272,0.00002437935,0.000009910047,0.00004980631,0.00007466559,0.00001411473],"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":[0.0001429496,0.00009401222,0.001063016,0.0001543218,0.00004263694,0.0001863481,0.0001382153,0.134127,0.06285883,0.210057,0.00969503,0.5814407],"study_design_scores_gemma":[0.00002440516,0.00006668237,0.0002883379,0.00001672166,0.00001306609,0.000287211,0.00002084894,0.9348927,0.01193369,0.02477208,0.02766574,0.00001858929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009581603,0.0001694917,0.9807072,0.00004651798,0.00007553092,0.00004169503,0.00003309212,0.0004729061,0.008872104],"genre_scores_gemma":[0.2010183,0.0003257107,0.7862207,0.0001022271,0.00005384689,0.0001342577,0.00031033,0.0002283652,0.0116062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004389499,"threshold_uncertainty_score":0.01468432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002823172642651345,"score_gpt":0.2241226381804099,"score_spread":0.2212994655377586,"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."}}