{"id":"W2373235700","doi":"","title":"Spatial Outlier Detection Based on Delaunay Triangulation","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Delaunay triangulation; Outlier; Computer science; Data mining; Spatial analysis; A priori and a posteriori; Artificial intelligence; Pattern recognition (psychology); Algorithm; Mathematics; Statistics","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":[0.001064945,0.0007156535,0.00127351,0.003032845,0.0008025297,0.00116267,0.00155295,0.0008166665,0.000879592],"category_scores_gemma":[0.007116002,0.000478841,0.0009989591,0.002965512,0.0008478577,0.00164005,0.001924124,0.0007178423,0.000472546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006142237,"about_ca_system_score_gemma":0.0009469024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006791164,"about_ca_topic_score_gemma":0.004904863,"domain_scores_codex":[0.9972103,0.0005688029,0.000191889,0.0006542159,0.001210984,0.0001638465],"domain_scores_gemma":[0.9974311,0.0008495823,0.0003925659,0.0003379473,0.0009099662,0.00007873738],"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":[0.0003036522,0.00007284476,0.01210957,0.000321653,0.0002178315,0.0005588306,0.0006575418,0.3647752,0.02503858,0.02374114,0.004472881,0.5677303],"study_design_scores_gemma":[0.00001210395,0.00003707549,0.001140151,0.00001306946,0.00001550664,0.0002440901,0.0001479062,0.9811888,0.006548876,0.007616535,0.003003129,0.00003276856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008347318,0.00008360214,0.9907658,0.00004757278,0.0000147473,0.00002903776,0.00005377747,0.0003447435,0.0003134879],"genre_scores_gemma":[0.1909615,0.0002338282,0.807465,0.0000274549,0.00002885823,0.0001109466,0.0003880639,0.00007993005,0.0007043922],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006791164,"threshold_uncertainty_score":0.01350331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01192625102362005,"score_gpt":0.1930393350760536,"score_spread":0.1811130840524335,"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."}}