{"id":"W4388570520","doi":"10.30525/978-9934-26-354-5-4","title":"DEBT POLICY DURING MARTIAL LAW AND POST-WAR RECONSTRUCTION","year":2023,"lang":"en","type":"article","venue":"","topic":"Economic Issues in Ukraine","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Debt; Martial law; State (computer science); Law; Economics; Political science; Finance; Politics","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":[0.001322,0.000104114,0.0001437293,0.0005981247,0.0020372,0.003721557,0.0005716011,0.001228412,0.003853403],"category_scores_gemma":[0.002909034,0.0001345952,0.0001703796,0.0006055959,0.0008433886,0.001301643,0.002306078,0.001758302,0.0005210442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005344201,"about_ca_system_score_gemma":0.004300296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01975165,"about_ca_topic_score_gemma":0.03078984,"domain_scores_codex":[0.9990606,0.0001651652,0.00005245929,0.00008274023,0.0002041904,0.0004350459],"domain_scores_gemma":[0.9992298,0.00007983963,0.0002464363,0.00002516178,0.0001432028,0.0002755406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007864403,0.0007596099,0.257541,0.0004444626,0.00008283114,0.0101246,0.03897399,0.003794417,0.005212221,0.3762836,0.07045783,0.235539],"study_design_scores_gemma":[0.00004428848,0.0003184382,0.5393356,0.0006558625,0.00002470438,0.001643364,0.04634212,0.002868538,0.001778539,0.0185506,0.3883699,0.00006800507],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8921115,0.004067011,0.0007529419,0.01313734,0.0003069926,0.00008318548,0.0005692747,0.00004025826,0.08893138],"genre_scores_gemma":[0.9848812,0.0007241872,0.0001454572,0.0008351938,0.0000724714,0.00001739484,0.0002261342,0.000009780999,0.01308828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01975165,"threshold_uncertainty_score":0.03927332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01566706546846627,"score_gpt":0.2167295305344311,"score_spread":0.2010624650659648,"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."}}