{"id":"W3132228528","doi":"10.1111/rssb.12415","title":"Nonparametric Density Estimation Over Complicated Domains","year":2021,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series B (Statistical Methodology)","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Nonparametric statistics; Regularization (linguistics); Computer science; Algorithm; Density estimation; Flexibility (engineering); Mathematical optimization; Mathematics; Artificial intelligence; Estimator; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001726346,0.0002778797,0.000657431,0.00002288885,0.0004421224,0.00009956061,0.0004364476,0.0002042329,0.003173226],"category_scores_gemma":[0.01151719,0.0002016601,0.0002677966,0.0006351285,0.00116068,0.0001268591,0.0005325112,0.0007873299,0.00007701969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003308173,"about_ca_system_score_gemma":0.0001089931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001864421,"about_ca_topic_score_gemma":0.00004426557,"domain_scores_codex":[0.9961651,0.001184391,0.000908176,0.0003879149,0.0008146159,0.0005398285],"domain_scores_gemma":[0.9928448,0.005775469,0.0005069479,0.0003596665,0.0001655897,0.0003475707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0009652816,0.001308566,0.04946597,0.0003054625,0.001127286,0.001063777,0.001489366,0.03221411,0.006799481,0.4136139,0.3513901,0.1402568],"study_design_scores_gemma":[0.001147261,0.0003391248,0.6594175,0.00004339465,0.0004685043,0.000500149,0.0002604917,0.06351952,0.0009730657,0.2615286,0.01132609,0.0004763454],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03212864,0.00005512018,0.9645416,0.00123199,0.000740774,0.0001466651,0.0002196531,0.00002186494,0.0009137303],"genre_scores_gemma":[0.1329177,0.00002736749,0.8653211,0.001195785,0.0000978938,0.00000443309,0.00002216782,0.00002495249,0.0003886238],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6099515,"threshold_uncertainty_score":0.997738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03781600939117122,"score_gpt":0.3089523970025555,"score_spread":0.2711363876113843,"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."}}