{"id":"W2189846386","doi":"10.19030/iber.v7i11.3303","title":"Tax Havens: Toward An Optimal Selection Approach Based On Multicriteria Analysis","year":2011,"lang":"en","type":"article","venue":"International Business & Economics Research Journal (IBER)","topic":"Taxation and Compliance Studies","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Tax haven; Haven; Selection (genetic algorithm); Economics; Safe haven; Public economics; Tax planning; Process (computing); Tax reform; Ad valorem tax; Microeconomics; Computer science; Tax avoidance; International economics; Artificial intelligence; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.008837705,0.001097814,0.002430382,0.003644297,0.001190311,0.002693502,0.001847791,0.001120205,0.003524862],"category_scores_gemma":[0.01682604,0.001118289,0.002125831,0.002890393,0.001499075,0.002521813,0.002698221,0.002188268,0.0003760773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001656326,"about_ca_system_score_gemma":0.003460635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005467758,"about_ca_topic_score_gemma":0.006373428,"domain_scores_codex":[0.9952791,0.003162316,0.0001673691,0.0005954215,0.0005676498,0.0002282431],"domain_scores_gemma":[0.9932626,0.004399483,0.0008037637,0.0004505229,0.0008727494,0.0002108677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001075173,0.0001562054,0.006440197,0.0001442365,0.000352262,0.0001890504,0.0003339577,0.6353435,0.0006724262,0.2566029,0.002074319,0.09758334],"study_design_scores_gemma":[0.00002678696,0.00004439382,0.0006384065,0.00003425892,0.00004792354,0.00004137477,0.00007523472,0.8817021,0.0002270174,0.1156799,0.001459116,0.00002346155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008649915,0.0001575862,0.989508,0.0002398493,0.00001281898,0.00006895064,0.00003277515,0.00005982114,0.001270192],"genre_scores_gemma":[0.3326238,0.000541558,0.6641002,0.0001417629,0.00009751395,0.0003121553,0.0002542775,0.0001254798,0.001803178],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008837705,"threshold_uncertainty_score":0.0467388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2270501135103974,"score_gpt":0.341738637651851,"score_spread":0.1146885241414535,"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."}}