{"id":"W1486234516","doi":"10.1007/978-1-4612-1358-1_27","title":"Variable Kernel Estimates: on the Impossibility of Tuning the Parameters","year":2000,"lang":"en","type":"book-chapter","venue":"Birkhäuser Boston eBooks","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Bandwidth (computing); Monotonic function; Mathematics; Convexity; Kernel density estimation; Counterexample; Smoothness; Variable (mathematics); Applied mathematics; Kernel (algebra); Mathematical optimization; Computer science; Mathematical analysis; Statistics; Discrete mathematics; Estimator","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01929208,0.001432118,0.002050033,0.001216718,0.001151204,0.003135381,0.003190094,0.005064206,0.003448679],"category_scores_gemma":[0.1023025,0.001376139,0.001018728,0.00113948,0.008670332,0.01110175,0.004713729,0.009457287,0.001703864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001188683,"about_ca_system_score_gemma":0.0007596807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008076044,"about_ca_topic_score_gemma":0.0004200652,"domain_scores_codex":[0.9900237,0.005434956,0.0004240976,0.001860071,0.001979981,0.0002772782],"domain_scores_gemma":[0.9252947,0.06283087,0.001775056,0.008352529,0.001502066,0.0002447746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002157956,0.00004685325,0.0007118129,0.0003532851,0.0000834872,0.0001090478,0.0003331903,0.03912774,0.00172315,0.8375853,0.008497499,0.111213],"study_design_scores_gemma":[0.00004641697,0.00003524293,0.0002695034,0.0001242674,0.0000251764,0.0001860442,0.00005456846,0.08723588,0.001681118,0.9026934,0.007603962,0.00004431644],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006425082,0.002141469,0.9778081,0.003166598,0.0001151722,0.00004337933,0.00009470517,0.0003443834,0.009861201],"genre_scores_gemma":[0.35068,0.003713607,0.6325278,0.002893135,0.0007281798,0.0006834714,0.0002564421,0.0009952041,0.007522041],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01929208,"threshold_uncertainty_score":0.1020274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1300486292535554,"score_gpt":0.3349943771966949,"score_spread":0.2049457479431396,"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."}}