{"id":"W6920244107","doi":"10.6068/dp14ba8284eb272","title":"Trend 1961 - 1997. Statistics Canada. CANSIM: Manufacturing - Nonmetallic Mineral and Metal | Country: Canada | Table: Principal statistics of the mineral industries | Variable: Total value added, Silver, lead, zinc mines | Units: , 1961-1997. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-153.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Mineral resource classification; Official statistics; Summary statistics; Statistical analysis; Census; Value (mathematics); Index (typography)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001808235,0.00238853,0.002442196,0.009015256,0.003165735,0.004582204,0.004613819,0.001357817,0.08250757],"category_scores_gemma":[0.01611883,0.00155058,0.001707785,0.0418703,0.0007082492,0.002268137,0.002066229,0.002892959,0.05157419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05018029,"about_ca_system_score_gemma":0.1340997,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.995122,"about_ca_topic_score_gemma":0.9933884,"domain_scores_codex":[0.9956349,0.0002312204,0.0004134768,0.0005957613,0.002074666,0.00105001],"domain_scores_gemma":[0.9697677,0.001122168,0.001050436,0.0008887684,0.02579863,0.00137239],"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":[0.00002151072,0.000006527941,0.001222819,0.0002316384,0.00002198741,0.00000846204,0.00002441945,0.0001399291,0.00001091129,0.0004970534,0.9961279,0.001686767],"study_design_scores_gemma":[0.0001037946,0.000009797616,0.02090944,0.0006193646,0.00005454243,0.00002453188,0.0004539395,0.0004134294,0.0001826238,0.0006019974,0.9765552,0.00007138873],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006264268,0.00005691429,0.00002867491,0.0001181469,0.00002467035,0.00001108065,0.9986895,0.00005609752,0.000952246],"genre_scores_gemma":[0.001087342,0.0003417733,0.0003914812,0.0001408783,0.00001733403,0.000089764,0.9928601,0.0001117445,0.004959533],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08250757,"threshold_uncertainty_score":0.3640851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02761491649669359,"score_gpt":0.2392859297640031,"score_spread":0.2116710132673096,"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."}}