{"id":"W6976918678","doi":"10.6068/dp1571d69f05969","title":"TREND: (IMF) International Monetary Fund. Historical Government Finance Statistics: Deficit/Surplus of Total Financing | Country: Argentina, Australia, Austria, Bahamas, Bahrain, Bangladesh, Barbados, Belgium, Belize, Benin, Bhutan, Bolivia, Botswana, Brazil, Bulgaria, Burkina Faso, Burma, Burundi, Cameroon, Canada, Cayman Islands, Central African Republic, Chad, Chile, Colombia, Comoros, Congo (Brazzaville), Congo (Kinshasa), Costa Rica, Cote D'Ivoire, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kenya, Kuwait, Lesotho, Liberia, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritius, Mexico, Morocco, Namibia, Nepal, Netherlands, Netherlands Antilles, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Romania, Rwanda, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Senegal, Seychelles, Sierra Leone, Singapore, Solomon Islands, Somalia, South Africa, South Korea, Spain, Sri Lanka, Sudan, Suriname, Swaziland, Sweden, Switzerland, Syria, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Uganda, United Arab Emirates, United Kingdom, United States, Uruguay, Vanuatu, Venezuela, Zambia, Zimbabwe | Government Entity: Central Government Consolidated Accounts | International Monetary Fund Subject: DEFICIT/SURPLUS, 1972 - 1989. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 056-005-001","year":2016,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); State (computer science); Public finance; CONQUEST; SAINT; Social security; Central government","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":[0.00110256,0.002303197,0.00110975,0.005306224,0.0006354967,0.005465497,0.001199585,0.001126948,0.08454821],"category_scores_gemma":[0.004343069,0.0007199727,0.0004864439,0.01406815,0.0003323859,0.00376982,0.001029543,0.002407332,0.1181375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001740429,"about_ca_system_score_gemma":0.003524986,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02837985,"about_ca_topic_score_gemma":0.01647759,"domain_scores_codex":[0.9990907,0.00009099746,0.0001469875,0.0001449797,0.0003946094,0.0001318441],"domain_scores_gemma":[0.9974081,0.0002001477,0.0006534118,0.0001032346,0.001493623,0.0001415059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007187662,0.00001484809,0.0009724665,0.0001997176,0.000007597018,0.00001355567,0.00001755272,0.00006066314,0.00004236056,0.0007983752,0.9854361,0.0123649],"study_design_scores_gemma":[0.00007741174,0.00002594202,0.01976036,0.0003545461,0.00002121361,0.00004721833,0.0001119052,0.0001936022,0.0002051491,0.0007344645,0.9784502,0.00001807161],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00250908,0.003864003,0.0004961879,0.002686932,0.002558408,0.0001876603,0.8780431,0.001785311,0.1078695],"genre_scores_gemma":[0.01291937,0.007638605,0.002400531,0.0007451911,0.0007105101,0.0005506487,0.8385624,0.001496352,0.1349763],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9716201,"threshold_uncertainty_score":0.2828419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0139621292080476,"score_gpt":0.239072412705326,"score_spread":0.2251102834972784,"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."}}