{"id":"W6976605173","doi":"10.6068/dp14ba8b6bf4874","title":"Trend 1976 - 2002. Statistics Canada. CANSIM: Labor - Nonwage Benefits | Country: Canada | Table: Registered pension plans (RPPs), members and market value of assets, by size of plan, sector, type of plan and contributory status | Variable: Members, males, Contributory registered pension plans, Size of plan, 10,000 to 29,999 members, Number | Units: #, 1976-2002. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-142.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Renewable Energy and Sustainability","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Payroll; Pension; Descriptive statistics; Census; Summary statistics; Social security; Economic statistics; Wages and salaries; Value (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.001980604,0.001410994,0.003322811,0.0001855911,0.0001737031,0.0001076058,0.001762074,0.001269667,0.00915521],"category_scores_gemma":[0.001824923,0.001384134,0.000002252398,0.0006274398,0.0006847946,0.0003369424,0.0008631674,0.0008755811,0.000003096844],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005023315,"about_ca_system_score_gemma":0.01053513,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9989514,"about_ca_topic_score_gemma":0.9973882,"domain_scores_codex":[0.9903201,0.001604678,0.002628191,0.001941273,0.002031073,0.001474674],"domain_scores_gemma":[0.9862306,0.005108757,0.002735752,0.004082346,0.0006647374,0.001177865],"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":[0.004475762,0.000212609,0.0006509938,0.003410057,0.001062569,0.0005424753,0.00002193764,0.0005850444,0.00007542799,0.00111027,0.9878075,0.00004541827],"study_design_scores_gemma":[0.004050925,0.0003914359,0.0002051302,0.0004291566,0.0009325134,0.0001748002,0.0005089433,0.0008374439,0.00000482177,0.000001358935,0.9911596,0.001303901],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001775412,0.005579671,0.000002570619,0.000007060067,0.000787782,0.001071257,0.9834676,0.00006357306,0.008842934],"genre_scores_gemma":[0.0008977446,0.002534467,0.0002446755,0.0001673852,0.0001206292,0.00002135508,0.9820175,0.000293886,0.0137024],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0100328,"threshold_uncertainty_score":0.999864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02190194953358748,"score_gpt":0.2414630671728111,"score_spread":0.2195611176392236,"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."}}