{"id":"W4399649316","doi":"10.32614/cran.package.klovan","title":"klovan: Geostatistics Methods and Klovan Data","year":2024,"lang":"en","type":"dataset","venue":"","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Nuclear Security Administration; U.S. Department of Energy","keywords":"Geostatistics; Computer science; Mathematics; Statistics; Spatial variability","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007166088,0.0003092683,0.0003064354,0.00005875083,0.00009564103,0.000193768,0.0008124728,0.0001796647,0.006862443],"category_scores_gemma":[0.0003481815,0.0002653308,0.00002194389,0.0001801618,0.0002375171,0.000102389,0.003817448,0.0004044742,0.007237138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005247609,"about_ca_system_score_gemma":0.00002421322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003492794,"about_ca_topic_score_gemma":0.001699332,"domain_scores_codex":[0.9980421,0.00008207907,0.0003135239,0.0009175273,0.0003108584,0.0003338784],"domain_scores_gemma":[0.9979491,0.0003682634,0.00008698488,0.001419625,0.000005761595,0.0001702563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001667734,0.00001349644,0.000009161731,0.00009965091,0.00003209048,0.00007321656,0.000009920986,0.000001655556,0.000007583824,0.0001217692,0.9487365,0.05089328],"study_design_scores_gemma":[0.00006683773,0.00002679628,0.0001568122,0.0000330507,0.0001765317,0.00003340895,0.00002612027,0.001786663,0.000003069138,0.003793957,0.9935457,0.0003511229],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[8.439904e-7,0.0003353478,0.02274226,0.0001355267,0.0007787762,0.0001662836,0.9719834,0.00004073078,0.003816836],"genre_scores_gemma":[6.338337e-7,0.0009324692,0.1787736,0.0004355567,0.00009392566,0.000006003266,0.8182598,0.00002121918,0.001476822],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1560314,"threshold_uncertainty_score":0.9999799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0424722792029983,"score_gpt":0.3709892886990823,"score_spread":0.328517009496084,"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."}}