{"id":"W4287870113","doi":"","title":"On the Estimation of Information Measures of Continuous Distributions","year":2023,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Statistical Mechanics and Entropy","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission","keywords":"Differential entropy; Mathematics; Lipschitz continuity; Bounded function; Entropy (arrow of time); Density estimation; Applied mathematics; Maximum entropy probability distribution; Probability density function; Kullback–Leibler divergence; Probability distribution; Joint entropy; Histogram; Uniform boundedness; Principle of maximum entropy; Mathematical analysis; Statistics; Computer science; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.001857813,0.0001451023,0.0002377213,0.00007826456,0.0001330618,0.00008611462,0.0004529452,0.00007363335,0.0001315265],"category_scores_gemma":[0.001291555,0.000119777,0.0001388287,0.0001969489,0.0001077276,0.00005939376,0.0003196835,0.0002737312,0.00003072482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002574588,"about_ca_system_score_gemma":0.0001049412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001110047,"about_ca_topic_score_gemma":0.00001763125,"domain_scores_codex":[0.9980077,0.000900634,0.0004743146,0.0001670722,0.0003085262,0.0001417824],"domain_scores_gemma":[0.9955984,0.001786152,0.0005695577,0.0008066075,0.001190439,0.0000488116],"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":[0.000004928505,0.0001319203,0.0001787482,0.00004019862,0.00005045544,4.752092e-8,0.0007820287,0.0004502191,0.00007867345,0.9679929,0.0009855725,0.02930431],"study_design_scores_gemma":[0.0005614323,0.000001496603,0.004057407,0.001827259,0.0001135119,2.7178e-7,0.0003483933,0.2929888,0.048717,0.6497689,0.00130217,0.0003133089],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03518397,0.00001836246,0.9510689,0.002522459,0.000138321,0.0003139506,0.001017919,0.00004003257,0.009696111],"genre_scores_gemma":[0.991946,0.00001391921,0.006446212,0.00001034097,0.000008431092,0.00005763738,0.001182084,0.0000119015,0.000323491],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.956762,"threshold_uncertainty_score":0.4884363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02079968478470742,"score_gpt":0.2398414928083918,"score_spread":0.2190418080236844,"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."}}