{"id":"W6958001476","doi":"10.6068/dp14ba80aa43448","title":"Trend 2001 - 2012. Statistics Canada. CANSIM: Labor - Industries | Country: Canada | Table: Average weekly earnings (SEPH), by type of employee for selected industries classified using the North American Industry Classification System (NAICS) | Variable: All employees, Waste collection, Excluding overtime | Units: Current $CAD, 2001-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-139.","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; Earnings; Overtime; Census; Summary statistics; Official statistics; Business statistics; Wages and salaries; 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":[0.002004101,0.002413856,0.00262195,0.008162249,0.003250978,0.004945718,0.005239252,0.001548235,0.09414158],"category_scores_gemma":[0.0179435,0.001664897,0.001995021,0.03999837,0.0005790601,0.002560962,0.002283566,0.00294733,0.06545175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04357025,"about_ca_system_score_gemma":0.1085111,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9927695,"about_ca_topic_score_gemma":0.9907415,"domain_scores_codex":[0.9962174,0.0002546824,0.000396921,0.0005518784,0.001641779,0.0009372997],"domain_scores_gemma":[0.9666411,0.001242521,0.0009877364,0.001071038,0.02848987,0.001567747],"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":[0.00002306903,0.000005797317,0.0009368842,0.0002000656,0.00001731206,0.000005846213,0.00001904096,0.00008933394,0.00000834882,0.0002850381,0.9969108,0.001498526],"study_design_scores_gemma":[0.0001496863,0.00001141069,0.02166882,0.0007762508,0.00005960506,0.00002413048,0.0004203564,0.0004459075,0.0001672129,0.0006322236,0.9755594,0.00008500413],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004374121,0.00003679742,0.00002035927,0.00009536099,0.00002085188,0.00001055758,0.9990708,0.00005615063,0.0006454026],"genre_scores_gemma":[0.0005790017,0.0001907185,0.0002864873,0.0001121269,0.00001433126,0.00009242177,0.9956354,0.00009777607,0.002991671],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09414158,"threshold_uncertainty_score":0.3161258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07417371302683728,"score_gpt":0.288565413785968,"score_spread":0.2143917007591307,"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."}}