{"id":"W4416785436","doi":"10.28924/2291-8639-23-2025-321","title":"Fixed Point Maximum Likelihood Estimation for the Epanechnikov-Pareto Distribution","year":2025,"lang":"","type":"article","venue":"International Journal of Analysis and Applications","topic":"Control Systems and Identification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimator; Maximum likelihood; Reliability (semiconductor); Point estimation; Confidence interval; Convergence (economics); Interval estimation; Estimation theory; Interval (graph theory); Maximum likelihood sequence estimation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008813372,0.000180293,0.0003757252,0.0004794143,0.0002721979,0.0004646156,0.0004925359,0.0001048339,0.00003213562],"category_scores_gemma":[0.0001387957,0.0001457479,0.0005375476,0.0008516642,0.00005699696,0.0002682551,0.00005049554,0.0001865539,0.000004634841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002562025,"about_ca_system_score_gemma":0.00008910616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001075685,"about_ca_topic_score_gemma":0.0001102975,"domain_scores_codex":[0.9980496,0.00003886611,0.001174142,0.0002104713,0.0003613986,0.0001654936],"domain_scores_gemma":[0.9971382,0.0004298768,0.0006638227,0.0002879662,0.0014069,0.00007321608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001848357,0.0003818417,0.002339767,0.000153021,0.02113594,0.000001736916,0.0003046988,0.0555926,0.006522203,0.06541327,0.009003597,0.8389665],"study_design_scores_gemma":[0.001352838,0.00005427567,0.03843179,0.0001803975,0.008825406,0.00002004893,0.0005409898,0.8002231,0.001173598,0.02421493,0.1247085,0.000274094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002974793,0.003608457,0.9844232,0.007295895,0.0006052403,0.0005943461,0.0003274892,0.00001598127,0.0001545976],"genre_scores_gemma":[0.9961597,0.001516639,0.00112773,0.00006127631,0.0004891755,0.0002124065,0.0002402171,0.00001064668,0.0001821742],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9931849,"threshold_uncertainty_score":0.5943425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004877808270980469,"score_gpt":0.2592929601521475,"score_spread":0.2544151518811671,"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."}}