{"id":"W2965600286","doi":"10.1007/s11053-019-09535-z","title":"Dynamics Behind Cycles and Co-movements in Metal Prices: An Empirical Study Using Band-Pass Filters","year":2019,"lang":"en","type":"article","venue":"Natural Resources Research","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Economics; Base metal; Hodrick–Prescott filter; Offset (computer science); Econometrics; Metal; Monetary economics; Macroeconomics; Business cycle; Metallurgy; Materials science; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003525091,0.0001848858,0.0004431669,0.0006752038,0.0001825777,0.0002738062,0.0004454255,0.0001518887,0.0002280499],"category_scores_gemma":[0.0002182301,0.0001823076,0.00006266528,0.0004394173,0.000126635,0.0003730431,0.0002467004,0.0008706682,0.0000233143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003778069,"about_ca_system_score_gemma":0.00002591314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002244507,"about_ca_topic_score_gemma":0.001899524,"domain_scores_codex":[0.9976012,0.0002049536,0.0005517658,0.0007531624,0.0002841826,0.0006047944],"domain_scores_gemma":[0.9988992,0.0002914084,0.0001356116,0.0004489108,0.0000681788,0.0001567094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001126009,0.0002741833,0.9960384,0.00003588338,0.00004015197,0.000009088172,0.002334456,0.00002074478,0.0000496505,0.0001766891,0.000007581979,0.0009005935],"study_design_scores_gemma":[0.0007393241,0.000208681,0.6438102,0.00001121846,0.000001469065,0.000001036959,0.001887523,0.3512454,0.000003647064,0.001376806,0.0005468154,0.000167932],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933099,0.0005865089,0.000009736686,0.0000989343,0.0001067411,0.000757428,0.00009875276,0.00001390099,0.005018126],"genre_scores_gemma":[0.9988705,0.00003050834,0.0001342129,0.00003964045,0.00003537144,0.00001232976,0.00003117392,0.0000251889,0.0008211021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3522282,"threshold_uncertainty_score":0.7434288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0918108803911863,"score_gpt":0.3899186659597941,"score_spread":0.2981077855686078,"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."}}