{"id":"W4367056862","doi":"10.1016/j.jmva.2023.105190","title":"Predictive density estimators with integrated <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\" id=\"d1e755\" altimg=\"si27.svg\"><mml:msub><mml:mrow><mml:mi>L</mml:mi></mml:mrow><mml:mrow><mml:mn>1</mml:mn></mml:mrow></mml:msub></mml:math> loss","year":2023,"lang":"lv","type":"article","venue":"Journal of Multivariate Analysis","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Mathematics; Estimator; Density estimation; Equivariant map; Combinatorics; Algorithm; Statistics; Discrete mathematics; Pure mathematics","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":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity","insufficient_payload"],"category_scores_codex":[0.003830007,0.00093128,0.00073602,0.001065618,0.00122478,0.001230195,0.001815376,0.001812774,0.2028918],"category_scores_gemma":[0.00790791,0.001391759,0.002276408,0.003052986,0.001409842,0.001215823,0.001267786,0.002364171,0.001073756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003614433,"about_ca_system_score_gemma":0.001744699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002368581,"about_ca_topic_score_gemma":0.001441449,"domain_scores_codex":[0.9899303,0.0009557609,0.002714078,0.001419831,0.00297276,0.002007304],"domain_scores_gemma":[0.987675,0.004659125,0.003880581,0.001856452,0.0005799989,0.001348867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004268164,0.0009908831,0.000263224,0.001650537,0.01685328,0.006469144,0.005375912,0.008689707,0.002707388,0.8120701,0.1364918,0.004169904],"study_design_scores_gemma":[0.001972156,0.001923146,0.0009734672,0.001667762,0.009367443,0.0009707108,0.002707943,0.493124,0.4849055,0.0005736011,0.0005715754,0.001242736],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7864274,0.0005150345,0.08402494,0.0008572863,0.002038922,0.00006154225,0.0008673806,0.0002173449,0.1249902],"genre_scores_gemma":[0.9558098,0.000885558,0.03984576,0.0005782256,0.00120781,0.0002432127,0.000644011,0.0005129423,0.0002726263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8114965,"threshold_uncertainty_score":0.9999374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02653477127786561,"score_gpt":0.2866784433335534,"score_spread":0.2601436720556877,"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."}}