{"id":"W6958426152","doi":"10.6068/dp14ba83ee11b22","title":"Trend 1973 - 2010. Statistics Canada. CANSIM: Education, Training and Learning - Education Finance | Country: Canada | Table: School board expenditures, by function and economic classification | Variable: Salary and wages expenditures, Adult education expenditures | Units: $CAD x 1,000, 1973-2010. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-068.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Salary; Statistics education; Economic statistics; Census; Revenue; Government (linguistics); Descriptive statistics; Official statistics; Personal income; Socioeconomic status","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":[0.001946399,0.002428482,0.002618284,0.009795446,0.00316915,0.005050712,0.004555437,0.001426164,0.08480479],"category_scores_gemma":[0.01561022,0.001733799,0.002024794,0.0444642,0.0006654572,0.002696588,0.002173125,0.003264745,0.05046334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0684954,"about_ca_system_score_gemma":0.1714894,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.996053,"about_ca_topic_score_gemma":0.994701,"domain_scores_codex":[0.9953573,0.000231488,0.0004270594,0.0005140292,0.002354245,0.001115815],"domain_scores_gemma":[0.9667531,0.0009166293,0.001059352,0.000755934,0.02888575,0.00162923],"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":[0.00002172845,0.000007078861,0.001148755,0.0002337134,0.00001908302,0.000007337084,0.00001992212,0.0001153224,0.000008918631,0.0004352422,0.996107,0.0018758],"study_design_scores_gemma":[0.0001169734,0.00001164545,0.02709391,0.0007263328,0.00006274795,0.00002694785,0.0004242341,0.0004281877,0.0001731573,0.00056882,0.9702924,0.00007452817],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007323135,0.00008709352,0.00002892482,0.0001705566,0.00003921961,0.00001788021,0.9980963,0.00006739854,0.001419416],"genre_scores_gemma":[0.001427715,0.0005304873,0.0004939071,0.0002169751,0.00003004873,0.0001340204,0.9891239,0.0001482329,0.007894635],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08480479,"threshold_uncertainty_score":0.4969712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02069446623206494,"score_gpt":0.2486019106795904,"score_spread":0.2279074444475255,"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."}}