{"id":"W4380303411","doi":"10.1109/icarc57651.2023.10145702","title":"Evaluating the economic disparities in the world: Sentiment Analysis on Central Bank Speeches from Third World and First World Countries","year":2023,"lang":"en","type":"article","venue":"","topic":"Media Influence and Politics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Central bank; Third world; Developing country; Sentiment analysis; World economy; Economy; Political science; Economics; Development economics; Economic growth; Artificial intelligence; Computer science; Monetary policy; Macroeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002047495,0.0002351042,0.0003152505,0.00256462,0.0006677547,0.001447518,0.0001120182,0.0002329243,0.001125696],"category_scores_gemma":[0.005106396,0.00006650956,0.0002104365,0.002780813,0.0004579048,0.0008437696,0.0009592524,0.0003595126,0.0002579695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008570783,"about_ca_system_score_gemma":0.0004711369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01132419,"about_ca_topic_score_gemma":0.01916732,"domain_scores_codex":[0.9992586,0.0002978598,0.00007626494,0.00005707002,0.0002289984,0.00008125881],"domain_scores_gemma":[0.9961786,0.001487105,0.0009543793,0.0001187645,0.001044047,0.0002169559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001399687,0.0002950382,0.8051434,0.0004956369,0.0002273955,0.0006492816,0.04267662,0.001420589,0.02252724,0.001686182,0.00708324,0.1163957],"study_design_scores_gemma":[0.00001306062,0.0001794942,0.9518378,0.00008610772,0.00005505945,0.0001320427,0.03596558,0.002665343,0.002547355,0.0002699751,0.006220918,0.0000274301],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951443,0.0001264935,0.0002282936,0.0001287667,0.00001946835,0.00002307139,0.0006875065,0.000006969997,0.003635073],"genre_scores_gemma":[0.9972721,0.0001885315,0.0005597927,0.00003966806,0.00002582294,0.00002973114,0.001223254,0.000006833371,0.0006543741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01132419,"threshold_uncertainty_score":0.02251655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06809737984681034,"score_gpt":0.3783350440770435,"score_spread":0.3102376642302332,"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."}}