{"id":"W6958031615","doi":"10.6068/dp14ba812ce5d18","title":"Trend 1994 - 2008. Statistics Canada. CANSIM: Environment - Natural Resources | Country: Canada | Table: Principal statistics of mineral industries, by North American Industry Classification System (NAICS) | Variable: Production workers' hours paid, Metal ore mining | Units: Hours x 1,000, 1994-2008. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-086.","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; Census; Official statistics; Natural resource; Mineral resource classification; Summary statistics; Production (economics)","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":[0.002050335,0.002292097,0.002645302,0.009293675,0.003427004,0.005107665,0.004804946,0.001437584,0.1016086],"category_scores_gemma":[0.01824797,0.001792119,0.001924304,0.04362763,0.0006544661,0.002877405,0.002399932,0.003218613,0.06712715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05283626,"about_ca_system_score_gemma":0.1508547,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944611,"about_ca_topic_score_gemma":0.9924738,"domain_scores_codex":[0.9954921,0.0002868115,0.000456513,0.0005861,0.00211572,0.001062792],"domain_scores_gemma":[0.9625914,0.001310735,0.001028285,0.001103933,0.03234283,0.001622829],"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":[0.0000164931,0.000004952043,0.000823978,0.0001756589,0.00001624753,0.000005247026,0.00001773439,0.00008946069,0.000007150431,0.0003544757,0.9971139,0.001374661],"study_design_scores_gemma":[0.0001140498,0.000008980968,0.01801679,0.0006873017,0.00005386737,0.00002188633,0.0004254791,0.0004342027,0.0001501389,0.000668235,0.9793401,0.00007911733],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004919958,0.00004605044,0.00002860763,0.0001324131,0.00003011083,0.00001415617,0.9985066,0.00007374752,0.001119096],"genre_scores_gemma":[0.0008682642,0.0002955528,0.0004754913,0.0001711416,0.00001953729,0.0001354978,0.9927557,0.0001569024,0.005121967],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1016086,"threshold_uncertainty_score":0.3833557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02592105051963425,"score_gpt":0.2303516931470217,"score_spread":0.2044306426273875,"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."}}