{"id":"W4226036023","doi":"10.1109/tac.2022.3142121","title":"Quadratic signaling with prior mismatch at an encoder and decoder: equilibria, continuity, and robustness properties","year":2022,"lang":"en","type":"article","venue":"Bilkent University Institutional Repository (Bilkent University)","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Stackelberg competition; Affine transformation; Mathematical optimization; Robustness (evolution); Computer science; Encoder; Gaussian; Probabilistic logic; Prior probability; Observability; Nash equilibrium; Mathematics; Mathematical economics; Applied mathematics; Artificial intelligence; Bayesian probability","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005466108,0.001615504,0.001926805,0.0009101571,0.00104384,0.002820265,0.002492857,0.003126119,0.004353928],"category_scores_gemma":[0.03194368,0.0008984071,0.001420715,0.0009999598,0.00366267,0.005274285,0.0038237,0.003551287,0.000772214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003100204,"about_ca_system_score_gemma":0.002130741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002085125,"about_ca_topic_score_gemma":0.0009046622,"domain_scores_codex":[0.9952887,0.001858521,0.0002290545,0.001055808,0.0009581638,0.0006096116],"domain_scores_gemma":[0.9837986,0.01079428,0.002594616,0.00115915,0.001021507,0.0006318364],"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":[0.000415083,0.0001474395,0.0009819192,0.0001347027,0.0001132736,0.0004745879,0.0004421343,0.3617271,0.005669204,0.6183419,0.000860257,0.01069238],"study_design_scores_gemma":[0.00006190391,0.0001533954,0.0002666436,0.00003600198,0.00003047242,0.0001190799,0.00009569705,0.7274975,0.00279988,0.2683646,0.0005273439,0.00004753477],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1192052,0.0001425334,0.8666683,0.001461168,0.0000352552,0.0001236041,0.000235135,0.0002537631,0.01187496],"genre_scores_gemma":[0.9407487,0.0001788552,0.05270364,0.0001865916,0.00004090517,0.0001977248,0.0001184093,0.00006609946,0.005759001],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005466108,"threshold_uncertainty_score":0.02890784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01307233171328697,"score_gpt":0.1685586840183305,"score_spread":0.1554863523050436,"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."}}