{"id":"W4387776371","doi":"10.1017/s0269964823000189","title":"On Jensen- divergence measure","year":2023,"lang":"en","type":"article","venue":"Probability in the Engineering and Informational Sciences","topic":"Statistical Mechanics and Entropy","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Divergence (linguistics); Measure (data warehouse); Kullback–Leibler divergence; Mathematics; Alpha (finance); Similarity measure; Entropy (arrow of time); Combinatorics; Applied mathematics; Statistics; Computer science; Artificial intelligence; Physics; Data mining; Psychometrics","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":[0.000535937,0.00003931434,0.00003514798,0.00003085327,0.00009345579,0.00003960741,0.00009678125,0.000006767996,0.00003077381],"category_scores_gemma":[0.00007728561,0.00002423431,0.00001081983,0.0002513184,0.00003175808,0.00009083374,0.00001930385,0.00005361479,0.0000260426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003701472,"about_ca_system_score_gemma":0.000009641244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001595545,"about_ca_topic_score_gemma":2.032933e-7,"domain_scores_codex":[0.9995736,0.000007912474,0.00008525218,0.00005654521,0.0001711984,0.0001054228],"domain_scores_gemma":[0.9997205,0.000199191,0.00001176793,0.00004090263,0.0000105291,0.0000171316],"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":[8.446826e-7,0.00000541539,0.0008289145,0.000004811027,9.810174e-7,4.33699e-8,0.0003170716,0.07577952,0.000003798057,0.9210989,0.00009593256,0.001863805],"study_design_scores_gemma":[0.00004771261,0.00002391036,0.007833343,0.00001054408,7.147989e-7,2.272127e-7,0.0001745236,0.8295289,0.00001203436,0.1620663,0.0002560899,0.00004566234],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927503,0.000005397195,0.002763218,0.0007007864,0.0001122396,0.0001064299,0.00001694,0.0000253084,0.003519337],"genre_scores_gemma":[0.999797,9.933586e-7,0.0001262129,0.0000313318,0.0000198131,0.00001506993,0.000003534171,6.602235e-7,0.000005309056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7590325,"threshold_uncertainty_score":0.09882464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02148259063914023,"score_gpt":0.2396108140244009,"score_spread":0.2181282233852607,"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."}}