{"id":"W4321251958","doi":"10.52851/cakrawala.v6i1.225","title":"Analisa Atas Besaran Underground Economy di Indonesia Pada Tahun 2016-2021 Dengan Pendekatan Moneter","year":2023,"lang":"en","type":"article","venue":"Cakrawala Repositori IMWI","topic":"SMEs Development and Digital Marketing","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Currency; Economics; Ordinary least squares; Inflation (cosmology); Quarter (Canadian coin); Econometrics; Gross domestic product; Value (mathematics); Economy; Regression analysis; Mathematics; Statistics; Monetary economics; Macroeconomics; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009442486,0.0002848514,0.0003204192,0.0001896416,0.001082254,0.0009068567,0.0005178782,0.0002149015,0.0001001434],"category_scores_gemma":[0.0002023288,0.0002958521,0.0001655473,0.0009132312,0.0002022643,0.0009758837,0.0002195674,0.0002242111,0.0003219771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004055691,"about_ca_system_score_gemma":0.0004439293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001664265,"about_ca_topic_score_gemma":0.0006387975,"domain_scores_codex":[0.9973062,0.0002623338,0.0005031931,0.0006062043,0.0005203596,0.0008017166],"domain_scores_gemma":[0.9983969,0.0004855654,0.0002094817,0.0004235233,0.0001427902,0.0003416843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000079726,0.0001000389,0.8879814,0.00006776008,0.0002689647,0.0005596596,0.00905426,0.00001666403,0.0007604924,0.009984799,0.07803614,0.01309014],"study_design_scores_gemma":[0.001207838,0.00008697863,0.3130968,0.0001852642,0.0001037583,0.00003380183,0.01504968,0.000119369,0.001547948,0.004115763,0.6629041,0.00154871],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7424421,0.0003053968,0.00003445489,0.0009813108,0.003125732,0.0003937726,0.00001069368,0.0003317092,0.2523749],"genre_scores_gemma":[0.9836814,0.0001088941,0.00008743116,0.0001084479,0.001933193,0.00005106001,0.0001189106,0.00004111762,0.01386955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.584868,"threshold_uncertainty_score":0.9999493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02086175694922014,"score_gpt":0.2735092548910633,"score_spread":0.2526474979418431,"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."}}