{"id":"W4401935266","doi":"10.1177/0958305x241262504","title":"Unraveling the impact of financial stress and trade policy uncertainty on advancing renewable energy transition in the USA","year":2024,"lang":"en","type":"article","venue":"Energy & Environment","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"SAIT Polytechnic","funders":"","keywords":"Distributed lag; Renewable energy; Economics; Autoregressive model; Lag; Commodity; Econometrics; Natural resource economics; Macroeconomics; Finance; Engineering; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005162715,0.0002576214,0.0003316404,0.0002388191,0.0001074961,0.00005275074,0.00026127,0.0001140963,0.0001891199],"category_scores_gemma":[0.00002075882,0.0001978701,0.0001829011,0.0001709964,0.0001401721,0.0001434706,0.00003902993,0.0001677143,0.0000115135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004928822,"about_ca_system_score_gemma":0.00003488475,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02685325,"about_ca_topic_score_gemma":0.001916145,"domain_scores_codex":[0.9983498,0.0000698171,0.000588414,0.000526185,0.0000732564,0.0003925672],"domain_scores_gemma":[0.9991584,0.0001616696,0.0001755632,0.0004398835,8.093454e-7,0.00006367719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00002262571,0.0001040426,0.003163782,0.0000141636,0.00004545567,0.000008091374,0.00077999,0.9148366,0.0001936774,0.07680573,0.0001651918,0.003860648],"study_design_scores_gemma":[0.002301588,0.001225942,0.5816882,0.000357443,0.00006271823,0.0000272618,0.0006442499,0.179461,0.007375722,0.1015174,0.1237564,0.001582046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797986,0.003777364,0.0067356,0.00296525,0.0001662842,0.0001569983,0.0002885541,0.00001830592,0.006093023],"genre_scores_gemma":[0.9953099,0.003382914,0.00006751307,0.0007506151,0.00022251,0.00004573242,0.00003775692,0.00003001699,0.000152975],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7353755,"threshold_uncertainty_score":0.979627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01215013652442901,"score_gpt":0.2102946718186207,"score_spread":0.1981445352941917,"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."}}