{"id":"W6901465042","doi":"10.6068/dp14ba8d9472d27","title":"Trend 2007 - 2012. Statistics Canada. CANSIM: Labor - Wages, Salaries and Other Earnings | Country: Canada | Table: Labour statistics consistent with the System of National Accounts (SNA), by province and territory, job category and North American Industry Classification System (NAICS) | Variable: Non-metallic mineral mining and quarrying, Annual average number of hours worked for self-employed jobs | Units: , 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; Official statistics; Summary statistics; National accounts; Socioeconomic status; Immigration; Statistics education","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":[0.001840129,0.002550537,0.002865557,0.008650293,0.002841368,0.004783058,0.005141196,0.001513912,0.07731199],"category_scores_gemma":[0.01661186,0.001779742,0.001930773,0.04335131,0.000607156,0.002391187,0.00205351,0.003217469,0.05308489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05112577,"about_ca_system_score_gemma":0.1207749,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9940529,"about_ca_topic_score_gemma":0.9922863,"domain_scores_codex":[0.9957053,0.0002586332,0.0004247023,0.0005591505,0.002048133,0.001004157],"domain_scores_gemma":[0.9658016,0.001152861,0.001164194,0.0008838776,0.02956567,0.001431774],"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":[0.00002444489,0.000007500385,0.001035535,0.0001893965,0.00001976326,0.000005650207,0.00001615751,0.0001111205,0.000007982954,0.0002829246,0.99703,0.001269387],"study_design_scores_gemma":[0.0001941932,0.00001460013,0.03240322,0.0008273031,0.00006746451,0.00002690718,0.0004540141,0.0006514632,0.00022665,0.0006377804,0.9643961,0.0001004092],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005976861,0.00004059038,0.00001732709,0.00009382302,0.00002277364,0.00001101567,0.9990669,0.00005067796,0.0006371104],"genre_scores_gemma":[0.0007576201,0.0002013216,0.000256995,0.0001169744,0.00001662284,0.00008756951,0.9951833,0.00008407675,0.003295591],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07731199,"threshold_uncertainty_score":0.3709452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01591805456797769,"score_gpt":0.2366799664004735,"score_spread":0.2207619118324958,"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."}}