{"id":"W6901502362","doi":"10.6068/dp14ba90500f222","title":"Trend 1997 - 2013. Statistics Canada. CANSIM: Labor - Employment and Unemployment | Country: Canada | Table: Labour Force Survey estimates (LFS), employees by union status and National Occupational Classification (NOC-S) | Variable: Sales and service occupations not elsewhere classified, including occupations in travel and accommodation, attendants in recreation and sport as well as supervisors, Union coverage rate (by a collective agreement) | Units: % %, 1997-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-136.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Unemployment; Census; Economic statistics; Official statistics; Socioeconomic status; Summary statistics; Recreation; Occupational prestige; Descriptive 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":[0.002148905,0.002310666,0.003042973,0.007654913,0.003389429,0.004768304,0.005106127,0.001453674,0.08340888],"category_scores_gemma":[0.01592497,0.00199035,0.002228119,0.03596285,0.0005740955,0.00223893,0.002437358,0.003347008,0.04758137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05274763,"about_ca_system_score_gemma":0.1356025,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9962428,"about_ca_topic_score_gemma":0.9950675,"domain_scores_codex":[0.9957035,0.0002836338,0.0005015803,0.0005387214,0.001892423,0.001080104],"domain_scores_gemma":[0.9691282,0.001020617,0.001039574,0.0007342394,0.02634229,0.001735112],"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":[0.00003492932,0.000009832085,0.001508162,0.0003048727,0.00002795859,0.000007589673,0.00002953512,0.0001037213,0.00000874287,0.0002648123,0.9958118,0.001888004],"study_design_scores_gemma":[0.000314534,0.00002633458,0.05710833,0.001460472,0.0001277909,0.00004071551,0.0008745324,0.0006667673,0.0002318553,0.0006193662,0.9384088,0.0001204048],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000902513,0.00006258033,0.00002447854,0.0001258967,0.00003243573,0.00001964569,0.9987148,0.00005763257,0.0008722586],"genre_scores_gemma":[0.001142056,0.0003393728,0.0003428673,0.0001922796,0.0000234757,0.0001550016,0.9924919,0.000104361,0.005208671],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08340888,"threshold_uncertainty_score":0.3827126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05078687626444671,"score_gpt":0.2947588887514223,"score_spread":0.2439720124869755,"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."}}