{"id":"W4391239508","doi":"10.1186/s40854-023-00565-4","title":"Time and frequency dynamics between NFT coins and economic uncertainty","year":2024,"lang":"en","type":"article","venue":"Financial Innovation","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"York University","keywords":"Dynamics (music); Economics; Econometrics; Statistical physics; Physics; Acoustics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008136379,0.0001434776,0.0002294907,0.001265822,0.0003263437,0.001044588,0.0002554729,0.0004568658,0.002430358],"category_scores_gemma":[0.01377555,0.0001419572,0.0001940841,0.001198868,0.0004846726,0.001375063,0.0006817043,0.0004728982,0.0002520113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005453413,"about_ca_system_score_gemma":0.0001846312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003814715,"about_ca_topic_score_gemma":0.003238423,"domain_scores_codex":[0.9995798,0.00009067263,0.00003206913,0.00008775914,0.0001407004,0.00006889405],"domain_scores_gemma":[0.9938958,0.003316044,0.001778117,0.0001814719,0.0005609187,0.0002675461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005024134,0.00009906806,0.8972806,0.00009640764,0.0001591969,0.001050385,0.001708462,0.03793238,0.005726835,0.0207618,0.002583621,0.03209896],"study_design_scores_gemma":[0.00001200165,0.00008036658,0.8473296,0.00004640078,0.0000435384,0.0003124695,0.001910554,0.1311562,0.001263866,0.01417707,0.003595107,0.00007274988],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939367,0.0001926342,0.002457486,0.0003809683,0.00001671803,0.00000775806,0.0003561977,0.00002266272,0.002628835],"genre_scores_gemma":[0.999432,0.00003815599,0.0001818731,0.000009287649,0.00001224699,0.00000391495,0.0001212461,0.000003179248,0.0001979677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003814715,"threshold_uncertainty_score":0.008130312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01823124935500716,"score_gpt":0.229591350448918,"score_spread":0.2113601010939109,"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."}}