{"id":"W6939010022","doi":"10.6068/dp14ba807863963","title":"Trend 2000 - 2011. Statistics Canada. CANSIM: Population and Demography - Births and Deaths | Country: Canada | Table: Deaths, by cause, Chapter IV: Endocrine, nutritional and metabolic diseases (E00 to E90), age group and sex | Variable: Total, all ages, Thiamine deficiency, Males | Units: # Persons, 2000-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-159.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Demographic statistics; Population statistics; Population; Socioeconomic status; Life expectancy; Fertility; Summary statistics; Official statistics","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":[0.002101823,0.002118459,0.002436033,0.006298924,0.003222775,0.004029574,0.004661882,0.001376554,0.1039696],"category_scores_gemma":[0.01608994,0.001595611,0.00210313,0.02802093,0.0005192049,0.001995504,0.002217577,0.002994068,0.04928776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04563117,"about_ca_system_score_gemma":0.1179062,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944233,"about_ca_topic_score_gemma":0.993226,"domain_scores_codex":[0.9972639,0.0002227769,0.0003494692,0.0003595606,0.001168291,0.0006359972],"domain_scores_gemma":[0.974708,0.0008748452,0.0006243442,0.0007026341,0.02183751,0.00125266],"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":[0.00002687503,0.000006388409,0.001143385,0.0002977081,0.00002391425,0.000007840623,0.00003039934,0.00012859,0.0000100885,0.0003747908,0.995357,0.002593084],"study_design_scores_gemma":[0.000256401,0.00001709918,0.03113884,0.001317792,0.0001008066,0.00004659578,0.0006009645,0.0008125902,0.0001923505,0.0009643253,0.9644335,0.0001186721],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006988722,0.00006662653,0.00004468544,0.0001571897,0.00003989421,0.00002814239,0.9983836,0.00007894911,0.001131075],"genre_scores_gemma":[0.001317156,0.0004609253,0.0008106431,0.0002635871,0.00002592508,0.0002592848,0.991716,0.000149947,0.004996535],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1039696,"threshold_uncertainty_score":0.3478129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02054356442188903,"score_gpt":0.2374268700463364,"score_spread":0.2168833056244474,"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."}}