{"id":"W7029513097","doi":"","title":"İNŞAAT SEKTÖRÜ, FAİZ ORANI VE EKONOMİK BÜYÜME İLİŞKİSİNİN ANALİZİ: TÜRKİYE ÖRNEĞİ (2002-2019)","year":2019,"lang":"tr","type":"article","venue":"DergiPark (Istanbul University)","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reel; Endogeneity; Quarter (Canadian coin)","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":[0.0009807554,0.0004238417,0.000401705,0.001699708,0.0005537774,0.001944684,0.0006302095,0.0005651305,0.005561472],"category_scores_gemma":[0.002773969,0.0002742478,0.0009323503,0.004387622,0.0003396319,0.001046797,0.001200099,0.0011415,0.001004764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003001093,"about_ca_system_score_gemma":0.003529825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2523456,"about_ca_topic_score_gemma":0.205036,"domain_scores_codex":[0.9994771,0.00009697671,0.00005149854,0.00009373434,0.0001449434,0.0001358026],"domain_scores_gemma":[0.9985272,0.0003415734,0.0003857461,0.00006081143,0.0005846001,0.0001000033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000476861,0.00008724025,0.9266463,0.0004562272,0.0004926168,0.0006684109,0.00544717,0.006807304,0.0007461133,0.007067977,0.0139364,0.03716746],"study_design_scores_gemma":[0.00002137965,0.00008032589,0.9465905,0.0002126001,0.0001773476,0.0001220588,0.01745349,0.003516257,0.000749334,0.0008452786,0.03018352,0.00004785645],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.946085,0.003347871,0.002140132,0.002705722,0.0001347125,0.00009921959,0.02418211,0.00009471519,0.02121064],"genre_scores_gemma":[0.9701117,0.001035017,0.0009626855,0.0001248437,0.00003843632,0.0001057551,0.01327502,0.00002988038,0.01431673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2523456,"threshold_uncertainty_score":0.5017536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01575997246432365,"score_gpt":0.1729307697743799,"score_spread":0.1571707973100563,"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."}}