{"id":"W6939131353","doi":"10.6068/dp14ba86afc2095","title":"Trend 1986 - 2009. Statistics Canada. CANSIM: Transportation - Transportation by Rail | Country: Canada | Table: Railway transport survey, summary statistics on employment, by occupational categories and mainline companies | Variable: Total mainline companies, Working foremen, Average number of employees | Units: , 1986-2009. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-196.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Summary statistics; Census; Official statistics; Descriptive statistics; Statistical analysis; Social statistics; Business 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":[0.002126242,0.002176354,0.002537402,0.008460082,0.003410446,0.004629709,0.004625782,0.001352493,0.08045817],"category_scores_gemma":[0.0164848,0.001748416,0.001816232,0.04052347,0.0006045454,0.00263755,0.002147864,0.003089219,0.05425536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05806448,"about_ca_system_score_gemma":0.1526006,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.995867,"about_ca_topic_score_gemma":0.9941971,"domain_scores_codex":[0.9954336,0.0002942267,0.00045854,0.0005740196,0.002159861,0.001079747],"domain_scores_gemma":[0.9670446,0.0009735083,0.0009296725,0.0008485371,0.02875186,0.00145195],"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":[0.00002642963,0.00000785758,0.001265724,0.0002533865,0.00002009012,0.000007989772,0.00002785085,0.0001212056,0.00001142927,0.0004166427,0.9958661,0.001975232],"study_design_scores_gemma":[0.0001249133,0.00001426689,0.03239195,0.0008415396,0.00006999895,0.00002922984,0.0006238569,0.0004786362,0.0001784374,0.000570594,0.9645909,0.000085773],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006893989,0.00005638937,0.00003038224,0.0001275241,0.00003224766,0.00001720732,0.9985581,0.00005617601,0.001053168],"genre_scores_gemma":[0.001147646,0.0003757493,0.000504877,0.000169055,0.00002117449,0.0001393636,0.9914171,0.0001214785,0.006103473],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08045817,"threshold_uncertainty_score":0.4212892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03088804095407947,"score_gpt":0.2594654487365981,"score_spread":0.2285774077825186,"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."}}