{"id":"W4242882305","doi":"10.1108/oxan-db205473","title":"Global copper market hit by China's slowdown","year":2015,"lang":"en","type":"other","venue":"Emerald expert briefings","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Slowdown; China; Quarter (Canadian coin); Consumption (sociology); Payment; Revenue; Copper; Economic slowdown; Hedge; Production (economics); Tax revenue; Economics; Business; Agricultural economics; Economy; Finance; Geography; Economic growth; Metallurgy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006735239,0.0004119373,0.0003666971,0.00006814527,0.00004677021,0.00009989795,0.0002257944,0.000387213,0.01558422],"category_scores_gemma":[0.00002619272,0.0004272445,0.00007824296,0.000214213,0.00004175499,0.0001449877,0.00002751828,0.000198157,0.0006215659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001214805,"about_ca_system_score_gemma":0.00004679877,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006640416,"about_ca_topic_score_gemma":0.000208536,"domain_scores_codex":[0.9987248,0.00002003981,0.0002678067,0.0003256523,0.0003287488,0.0003329552],"domain_scores_gemma":[0.9994056,0.000007900183,0.00007329148,0.0002845674,0.00003896512,0.0001896314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000632531,0.00002127256,0.000001347161,0.00005118776,0.00007188528,0.000004787878,0.00009988085,0.00001974122,0.00008217357,0.00004642642,0.9988599,0.0007350151],"study_design_scores_gemma":[0.000301052,0.00001301168,0.000008617999,0.00006600478,0.000009818945,0.00001646835,0.000003788173,0.0003397805,0.00005343465,0.00003447915,0.9986591,0.0004944897],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000001927673,0.01406456,0.0005384492,0.01067637,0.0006065257,0.0001656758,0.0002279686,0.001630431,0.9720881],"genre_scores_gemma":[0.00004086774,0.001651444,0.0003821554,0.02727586,0.0005294711,0.00004518015,0.0003971428,0.0004153968,0.9692625],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01659948,"threshold_uncertainty_score":0.9999744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006830348798840777,"score_gpt":0.242078802236612,"score_spread":0.2352484534377712,"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."}}