{"id":"W3124669776","doi":"10.13106/jafeb.2014.vol1.no3.17.","title":"The Impact of Product Distribution and Information Technology on Carbon Emissions and Economic Growth: Empirical Evidence in Korea","year":2014,"lang":"en","type":"article","venue":"Journal of Asian Finance Economics and Business","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cointegration; Granger causality; Econometrics; Economics; Error correction model; Distribution (mathematics); Quarter (Canadian coin); Product (mathematics); Causality (physics); Gross domestic product; Resource (disambiguation); Short run; Macroeconomics; Mathematics; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005428629,0.0002280418,0.0001865177,0.001113941,0.0002050867,0.0008667071,0.0001747452,0.0002291154,0.001632926],"category_scores_gemma":[0.001593779,0.0001444465,0.0003542293,0.002005727,0.0004639868,0.0009431182,0.0005505439,0.0003797441,0.0001845321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005671984,"about_ca_system_score_gemma":0.0005957718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01571151,"about_ca_topic_score_gemma":0.02020555,"domain_scores_codex":[0.9997527,0.00006029264,0.0000294971,0.00004618717,0.00005686246,0.00005438671],"domain_scores_gemma":[0.9964148,0.001363194,0.001494949,0.0001115991,0.0003947324,0.0002206943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001405975,0.0001719536,0.9817433,0.0001058782,0.0001056115,0.0004675207,0.0002569675,0.001700867,0.0006532143,0.001048924,0.0002889838,0.01331617],"study_design_scores_gemma":[0.000007948443,0.00007429875,0.9948846,0.00003485073,0.00008977314,0.0001139564,0.001143207,0.001906835,0.0004835687,0.0002967891,0.0009566624,0.000007696082],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977053,0.0005575429,0.00008983359,0.0001070053,0.000001741337,0.000003174806,0.0001481608,0.000002333433,0.001384927],"genre_scores_gemma":[0.998809,0.0006987774,0.00005701242,0.00001577953,0.000002588083,0.00000167781,0.0001933479,0.000001096689,0.0002206044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01571151,"threshold_uncertainty_score":0.03124011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01791592379828076,"score_gpt":0.2243187827578686,"score_spread":0.2064028589595878,"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."}}