{"id":"W2885304536","doi":"10.5430/ijba.v9n5p62","title":"The Efficiency of Fiscal Incentive in Municipalities With Lower Human Development Indices: The Case of Maranhão","year":2018,"lang":"en","type":"article","venue":"International Journal of Business Administration","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Incentive; State (computer science); Business; Public economics; Economics; Microeconomics; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000632279,0.00007105486,0.0001691628,0.000157985,0.00008605055,0.00004564676,0.000329346,0.00003508555,0.00002940554],"category_scores_gemma":[0.00009310143,0.00004690572,0.00003935863,0.0001388337,0.0002881693,0.0002239126,0.00003334368,0.00008891843,0.000003163416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000699392,"about_ca_system_score_gemma":0.00008532873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002177762,"about_ca_topic_score_gemma":0.001099793,"domain_scores_codex":[0.9988793,0.00001779868,0.0008681706,0.00007977484,0.00006309332,0.00009186597],"domain_scores_gemma":[0.9985002,0.00008561376,0.001064134,0.00009429554,0.0002376105,0.00001819085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00215111,0.001169673,0.3130811,0.00008795367,0.0006162878,0.0003045185,0.01739882,0.0003538686,0.0001071076,0.6600786,0.0002869284,0.004364014],"study_design_scores_gemma":[0.003914414,0.001402305,0.9136304,0.0004513899,0.00002574529,0.0009602249,0.004805156,0.001798024,0.005473387,0.06289696,0.004259635,0.0003823374],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943561,0.00007900323,0.0003890574,0.0007331291,0.0002944392,0.00006126623,0.0000139421,0.00000103865,0.004072036],"genre_scores_gemma":[0.9996573,0.00001463148,0.00007379436,0.00003424988,0.0001534803,0.000002719253,0.000002842823,0.000004852025,0.00005617478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6005493,"threshold_uncertainty_score":0.191276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03432627981908222,"score_gpt":0.2691298433243097,"score_spread":0.2348035635052275,"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."}}