{"id":"W4318705717","doi":"10.3390/app13031784","title":"Kernel Density Derivative Estimation of Euler Solutions","year":2023,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Central South University","keywords":"Kernel density estimation; Spurious relationship; Mathematics; Euler's formula; Kernel (algebra); Probability density function; Algorithm; Density estimation; Variable kernel density estimation; Multivariate statistics; Applied mathematics; Estimator; Computer science; Kernel method; Statistics; Mathematical analysis; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00135066,0.000635062,0.0005987627,0.001035265,0.000276833,0.000814002,0.000720091,0.0006595348,0.0009283118],"category_scores_gemma":[0.007629177,0.0003275178,0.0007816275,0.0008410721,0.0004950711,0.001479131,0.0008356192,0.0009882654,0.0003156496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006957799,"about_ca_system_score_gemma":0.001492611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00940822,"about_ca_topic_score_gemma":0.00530316,"domain_scores_codex":[0.9995559,0.000116345,0.00003726791,0.0001080835,0.000132008,0.00005036801],"domain_scores_gemma":[0.9980647,0.0008716335,0.000194867,0.0002194841,0.0006026836,0.00004665164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001753957,0.0001028515,0.009164267,0.0001656975,0.0001058058,0.0001316925,0.0001922715,0.6587399,0.01388206,0.03376728,0.002661699,0.2809112],"study_design_scores_gemma":[0.000003722527,0.000004999081,0.0006233597,0.000003411621,0.000003758241,0.00001850243,0.000007253414,0.9952815,0.001509799,0.002113093,0.000423092,0.00000748629],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02122787,0.00009366464,0.9778701,0.00005611253,0.00001575163,0.00001629821,0.00005735283,0.0002920561,0.0003708262],"genre_scores_gemma":[0.507727,0.0003214712,0.4893182,0.00006113536,0.00003052053,0.00006846862,0.0005426579,0.0001810139,0.001749568],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00940822,"threshold_uncertainty_score":0.01870686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04423843907268621,"score_gpt":0.2704407045061659,"score_spread":0.2262022654334797,"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."}}