{"id":"W4402944784","doi":"10.1016/j.jeca.2024.e00387","title":"Relative prices and relative supplies in the UK beef meat industry: A wavelet cross-correlation analysis","year":2024,"lang":"en","type":"article","venue":"The Journal of Economic Asymmetries","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Economics; Wavelet; Econometrics; Agricultural economics; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001693411,0.0002228029,0.0004240848,0.001090002,0.0002053119,0.001265383,0.000410714,0.0006016648,0.002820449],"category_scores_gemma":[0.00849468,0.0003514545,0.0005247691,0.001456098,0.0004984112,0.00151213,0.0008858585,0.0008505446,0.0004164048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005639317,"about_ca_system_score_gemma":0.0003429478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01055322,"about_ca_topic_score_gemma":0.006212796,"domain_scores_codex":[0.9996197,0.0001120169,0.00002943148,0.00007614371,0.00008393567,0.00007874829],"domain_scores_gemma":[0.9957826,0.002900665,0.0004800374,0.0002441176,0.0004919618,0.0001006712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00252858,0.0004792766,0.5404454,0.0003042208,0.0008214972,0.001713983,0.002252718,0.2534305,0.02449193,0.03915649,0.002757255,0.1316181],"study_design_scores_gemma":[0.00003116776,0.0001350755,0.6197529,0.00003942794,0.0001654846,0.0002380878,0.0005709338,0.370497,0.001334823,0.006109515,0.001055935,0.00006942769],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932182,0.0002126682,0.005460036,0.0001048767,0.000007194971,0.000003825194,0.0001292382,0.00001344836,0.0008504341],"genre_scores_gemma":[0.9983925,0.0001274937,0.0006101418,0.000009113881,0.00001078117,0.000002944229,0.0002180548,0.00001000473,0.0006187828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01055322,"threshold_uncertainty_score":0.02098358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02158452307248781,"score_gpt":0.2652039187771434,"score_spread":0.2436193957046556,"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."}}