{"id":"W4402967590","doi":"10.30784/epfad.1512266","title":"Forecasting Green Technology Diffusion in OECD Economies Through Machine Learning Analysis","year":2024,"lang":"en","type":"article","venue":"Ekonomi Politika ve Finans Arastirmalari Dergisi","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive integrated moving average; Diffusion; Face (sociological concept); Economics; Economy; Economic geography; Time series; Development economics; Computer science; Machine learning; Social science; Sociology","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":[0.001476415,0.0004891211,0.0003129122,0.002389763,0.0002545645,0.001125169,0.0002401006,0.0004789123,0.0005978146],"category_scores_gemma":[0.004621821,0.0001321294,0.0006159968,0.001982603,0.0003193028,0.0009582763,0.0005298172,0.0006499767,0.0001834647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001581855,"about_ca_system_score_gemma":0.0009755935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06201952,"about_ca_topic_score_gemma":0.03176812,"domain_scores_codex":[0.99972,0.000115278,0.00001976592,0.00003494782,0.00005530927,0.00005458832],"domain_scores_gemma":[0.9982443,0.001087437,0.0002833035,0.00009017593,0.0002363557,0.00005845417],"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":[0.0001093583,0.0001189298,0.1843093,0.00006486934,0.0001064211,0.0003442086,0.0001670776,0.7737258,0.0004188441,0.003737655,0.001973425,0.03492414],"study_design_scores_gemma":[0.000009550446,0.00003812561,0.05573175,0.00003494704,0.00002251854,0.00003515845,0.0004176389,0.9374944,0.0006534106,0.003513487,0.002029369,0.00001965072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831471,0.0003382491,0.01023692,0.0005915926,0.0000217281,0.00003216218,0.001427862,0.0001390292,0.004065441],"genre_scores_gemma":[0.9924805,0.0004659827,0.005063668,0.00003272122,0.00001218405,0.00003079664,0.001431278,0.000008787057,0.0004741334],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06201952,"threshold_uncertainty_score":0.1233171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02382532744428971,"score_gpt":0.2166887579034403,"score_spread":0.1928634304591506,"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."}}