{"id":"W6920680459","doi":"10.6068/dp14ba7b6f12e68","title":"Trend 1976 - 2011. Statistics Canada. CANSIM: Economic Accounts - Environmental and Resource Accounts | Country: Canada | Table: Proven and probable iron reserves | Variable: Additions, proven and probable iron reserves (x 1,000,000) | Units: Tonnes, 1976-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-058.","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; Official statistics; National accounts; Summary statistics; Census; Resource (disambiguation); Natural resource; Socioeconomic status; Statistical analysis","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":[0.00188158,0.002229441,0.002454654,0.01046021,0.00326128,0.005715381,0.004238159,0.001429842,0.109994],"category_scores_gemma":[0.01663418,0.001762549,0.001721507,0.04785566,0.0006697729,0.003000566,0.002052654,0.003153099,0.0653423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06511007,"about_ca_system_score_gemma":0.155974,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946346,"about_ca_topic_score_gemma":0.9925303,"domain_scores_codex":[0.9955649,0.0002292511,0.0004000709,0.0004788334,0.002358997,0.0009679229],"domain_scores_gemma":[0.9655613,0.001112038,0.000954976,0.0008930295,0.03011444,0.001364201],"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":[0.00001374983,0.000004594871,0.0006665236,0.0001716947,0.00001416399,0.000006083176,0.00001793456,0.0001106795,0.000007855776,0.0005459429,0.9969363,0.001504484],"study_design_scores_gemma":[0.0000649319,0.000006321673,0.01450967,0.0004856242,0.00003649499,0.00001928293,0.0003638082,0.0003933337,0.0001397835,0.0005576576,0.9833578,0.00006521514],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005594339,0.00005908992,0.00002989689,0.0001406251,0.00003474668,0.00001641461,0.9979679,0.00007463556,0.001620762],"genre_scores_gemma":[0.001088445,0.0004374617,0.0004793017,0.0001520443,0.000023176,0.000133857,0.9890781,0.0001607779,0.008446778],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.109994,"threshold_uncertainty_score":0.4724088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01893642255319812,"score_gpt":0.2234403670127516,"score_spread":0.2045039444595535,"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."}}