{"id":"W3124651812","doi":"10.17016/feds.2016.044","title":"Nowcasting Turkish GDP and News Decomposition","year":2016,"lang":"en","type":"article","venue":"Finance and Economics Discussion Series","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nowcasting; Gross domestic product; Real gross domestic product; Turkish; Economics; Turkish economy; Quarter (Canadian coin); Econometrics; Econometric model; GDP deflator; Monetary economics; Macroeconomics; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001210068,0.0001533485,0.0002868426,0.0001154168,0.0002935141,0.0002567781,0.0001862143,0.00007625048,0.00009806948],"category_scores_gemma":[0.0009841679,0.0000717743,0.00004722532,0.0001155271,0.0001816903,0.00107397,0.0002573493,0.00005833211,0.00004298649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002410604,"about_ca_system_score_gemma":0.00002801311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000954234,"about_ca_topic_score_gemma":0.00009743153,"domain_scores_codex":[0.9985667,0.0001014576,0.0004686879,0.0005261872,0.00010666,0.0002303423],"domain_scores_gemma":[0.9985861,0.0007150209,0.0002547953,0.0003093692,0.00005132417,0.00008342035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001052692,0.000008038319,0.04412428,0.000003770203,0.000003848128,0.000001588694,0.0003170354,0.000008042729,0.0006693578,0.00297983,0.001857109,0.9499218],"study_design_scores_gemma":[0.001117482,0.0002742727,0.3935347,0.0002544926,0.00001537772,0.0002038208,0.001419646,0.001145085,0.003009892,0.222166,0.3761934,0.0006658611],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863068,0.0001100122,0.003535492,0.00694073,0.0004195207,0.00009678715,0.00003076905,0.00002643011,0.002533423],"genre_scores_gemma":[0.9729403,0.0007303525,0.01800397,0.0001720204,0.0001449479,0.00001613568,0.000001585117,0.00001668635,0.007974052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.949256,"threshold_uncertainty_score":0.2926871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05971806482376499,"score_gpt":0.3473345100607447,"score_spread":0.2876164452369797,"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."}}