{"id":"W6920292645","doi":"10.6068/dp14ba8735bd968","title":"Trend 1997 - 2013. Statistics Canada. CANSIM: Labor - Hours of Work and Work Arrangements | Country: Canada | Table: Labour force survey estimates (LFS), employees by job permanency, North American Industry Classification System (NAICS), sex and age group | Variable: 65 years and over, Goods-producing sector, Permanent, Males | Units: # Persons x 1,000, 1997-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-138.","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; Work (physics); Recreation; Economic statistics; Official statistics; Descriptive statistics; Summary statistics; Socioeconomic status; Wages and salaries; Statistician","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":[0.001985419,0.00231207,0.002763072,0.007029513,0.0027242,0.004177183,0.005266777,0.001345841,0.08480489],"category_scores_gemma":[0.01544886,0.001605757,0.002134918,0.03418216,0.0005007574,0.002014427,0.002143903,0.003139591,0.05212646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03789186,"about_ca_system_score_gemma":0.09407394,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9931026,"about_ca_topic_score_gemma":0.9912735,"domain_scores_codex":[0.9964072,0.0002512149,0.0004131229,0.0004915294,0.001547944,0.0008890081],"domain_scores_gemma":[0.9722846,0.001038412,0.0009244469,0.0007333748,0.02363503,0.001384128],"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":[0.00002874704,0.000008268698,0.001439668,0.0002696413,0.00002407877,0.000006342371,0.00002598552,0.0001016772,0.000007649958,0.0002388696,0.9960996,0.001749502],"study_design_scores_gemma":[0.0002505386,0.00002013997,0.04893405,0.001294393,0.00009863883,0.00003296097,0.0007805917,0.000574878,0.0001733715,0.000667395,0.9470674,0.0001057556],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006973051,0.00004514066,0.00002153757,0.00009585403,0.00002480052,0.00001366267,0.9990684,0.00004450227,0.0006163998],"genre_scores_gemma":[0.0007743286,0.0002256283,0.000268159,0.0001305038,0.0000162408,0.0001238074,0.9949839,0.00007060916,0.00340677],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08480489,"threshold_uncertainty_score":0.2837006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03085914595199168,"score_gpt":0.2522464866953637,"score_spread":0.221387340743372,"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."}}