{"id":"W4409557626","doi":"10.1007/s10614-025-10932-1","title":"Clean Energy Stock Market and Energy/Metals as Safe-Haven Assets: New Insights from Quantile-on-Quantile and Markov-Switching Approaches","year":2025,"lang":"en","type":"article","venue":"Computational Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Quantile; Markov chain; Safe haven; Econometrics; Stock (firearms); Quantile regression; Financial economics; Business; Economics; Mathematics; Statistics; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003186252,0.0003089861,0.0006118163,0.0003482945,0.0002252501,0.0003054264,0.0002343809,0.000178186,0.0002033313],"category_scores_gemma":[0.00009441579,0.0003785592,0.000111935,0.0001336565,0.00007443608,0.0003076543,0.0002115981,0.0001615455,0.000008872191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001200502,"about_ca_system_score_gemma":0.0001183927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001288496,"about_ca_topic_score_gemma":0.0005860224,"domain_scores_codex":[0.997994,0.00005060692,0.000831045,0.0008395138,0.00003798646,0.0002468601],"domain_scores_gemma":[0.998349,0.0007328577,0.0003990972,0.0003232305,0.00002572303,0.0001700885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001360705,0.00009227894,0.04075009,0.0000301824,0.0002667218,0.000001836463,0.0001182434,0.002387685,9.446338e-7,0.906438,0.001822168,0.04795577],"study_design_scores_gemma":[0.0004814626,0.00003061231,0.05449452,0.00001657693,0.00001009505,0.000001635028,0.00003435744,0.5484863,0.000003006538,0.3834004,0.0128154,0.0002256003],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8437574,0.001881855,0.09219421,0.001014042,0.0005176023,0.0001489665,0.0003772234,0.00004408802,0.06006464],"genre_scores_gemma":[0.9914898,0.0004858749,0.004645442,0.0009159818,0.0001106754,0.0000149696,0.0002330521,0.00003264107,0.002071569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5460986,"threshold_uncertainty_score":0.9998666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02889242201494416,"score_gpt":0.2225540626839598,"score_spread":0.1936616406690156,"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."}}