{"id":"W3015436684","doi":"","title":"A non-parametric estimator for the doubly-periodic Poisson intensity function","year":2007,"lang":"en","type":"article","venue":"Data Archiving and Networked Services (DANS)","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Centrum Wiskunde and Informatica; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Koninklijke Nederlandse Akademie van Wetenschappen; European Research Consortium for Informatics and Mathematics","keywords":"Estimator; Mathematics; Poisson distribution; Parametric statistics; Bounded function; Applied mathematics; Series (stratigraphy); Function (biology); Consistent estimator; Minimum-variance unbiased estimator; Parametric model; Window (computing); Realization (probability); Delta method; Statistics; Mathematical analysis; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00743134,0.0004582043,0.0009995222,0.001449162,0.000400229,0.0009893082,0.002066014,0.001344869,0.001348848],"category_scores_gemma":[0.036476,0.0005018598,0.0007896695,0.001289834,0.000981943,0.002031073,0.001680352,0.001728994,0.0004156455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005694219,"about_ca_system_score_gemma":0.001079637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000801173,"about_ca_topic_score_gemma":0.0008600328,"domain_scores_codex":[0.9972529,0.001349668,0.0001205318,0.0004524864,0.0006999149,0.0001246096],"domain_scores_gemma":[0.9844463,0.01033198,0.001402745,0.002116544,0.001523345,0.0001789527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002720017,0.0003791737,0.03629033,0.0003520437,0.0003975092,0.0004202422,0.0003781076,0.2595731,0.01670058,0.225463,0.003381394,0.4563925],"study_design_scores_gemma":[0.000034361,0.0001019697,0.006176267,0.00003482963,0.00005002912,0.0004178294,0.00005957394,0.9301855,0.004141599,0.05648464,0.002245447,0.00006799944],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01002635,0.00008591677,0.9892932,0.00007710385,0.00001451723,0.00003089018,0.00005490498,0.00009529629,0.000321752],"genre_scores_gemma":[0.3415742,0.0002916192,0.6551906,0.0001186347,0.0001023337,0.0003084869,0.0006531128,0.00009266926,0.001668295],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00743134,"threshold_uncertainty_score":0.03930116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01744544326068104,"score_gpt":0.2499521156598184,"score_spread":0.2325066723991374,"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."}}