{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000660154,0.00009513165,0.00008601588,0.00009413673,0.000318513,0.00002876963,0.00008634981,0.00005808251,0.0001206178],"category_scores_gemma":[7.156015e-7,0.00008071669,0.00005476081,0.0001717438,0.00003034295,0.0000449405,0.000002755556,0.00008929911,0.0005430332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006074335,"about_ca_system_score_gemma":0.00002328533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006404842,"about_ca_topic_score_gemma":0.0004664426,"domain_scores_codex":[0.9993352,0.00003648342,0.0001431993,0.0002257274,0.0001173037,0.0001420386],"domain_scores_gemma":[0.9996078,0.00006695288,0.00004796794,0.0001776747,0.00003195217,0.00006764304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002623067,0.0000311663,0.01066656,0.000002869728,0.000004836339,0.000002243901,0.0000671128,0.01502511,0.000339068,0.000003384772,0.0003720215,0.9734594],"study_design_scores_gemma":[0.0004800649,0.00007640104,0.4381825,0.000005142541,0.000008955781,0.00002854014,0.000003812077,0.3833242,0.001921289,0.00009007203,0.175714,0.000164957],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1701466,0.00002228434,0.8254951,0.0001737696,0.00005910721,0.0003608572,0.00001723805,0.0001295603,0.003595565],"genre_scores_gemma":[0.9796311,0.00000431945,0.0193063,0.000440367,0.0003234126,0.000002412241,0.0001535308,0.000004092795,0.0001344889],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9732944,"threshold_uncertainty_score":0.6979774,"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."}}