{"id":"W6939229719","doi":"10.6068/dp14ba8c7ddc688","title":"Trend 2007 - 2012. Statistics Canada. CANSIM: Labor - Wages, Salaries and Other Earnings | Country: Canada | Table: Labour statistics by business sector industry and by non-commercial activity consistent with the industry accounts | Variable: Total compensation for all jobs, Agencies, brokerages and other insurance related activities | Units: $CAD x 1,000, 2007-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-145.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Economic statistics; Census; Wages and salaries; Summary statistics; Official statistics; Socioeconomic status; 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":[0.001821836,0.002565995,0.002667679,0.008251154,0.002980275,0.004756766,0.00518057,0.001520952,0.0886069],"category_scores_gemma":[0.01510879,0.001772908,0.001801918,0.03912407,0.0006123483,0.002388036,0.00218572,0.003057272,0.05871662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04937414,"about_ca_system_score_gemma":0.1145969,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9940082,"about_ca_topic_score_gemma":0.9923387,"domain_scores_codex":[0.9961234,0.0002347145,0.000357261,0.0005039413,0.001792282,0.0009884537],"domain_scores_gemma":[0.9708524,0.001054434,0.001019253,0.0008170283,0.02475535,0.001501428],"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":[0.00002054606,0.000006884201,0.0008993311,0.0001626779,0.00001488696,0.000005497087,0.00001613356,0.0001025952,0.000007055176,0.0002898544,0.9971009,0.001373679],"study_design_scores_gemma":[0.0001607532,0.00001207224,0.02525213,0.0007610145,0.00005366608,0.00002417036,0.0004614778,0.0005671277,0.000203081,0.0006475591,0.9717674,0.00008953406],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005612852,0.00004077047,0.00002008029,0.0001044164,0.00002134421,0.00001096965,0.9989432,0.00005688376,0.000746213],"genre_scores_gemma":[0.0007398652,0.0002237319,0.0002919625,0.0001192847,0.00001509837,0.00008803696,0.9945176,0.00009476331,0.003909583],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0886069,"threshold_uncertainty_score":0.3582362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02290163182297135,"score_gpt":0.2399172364374157,"score_spread":0.2170156046144444,"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."}}