{"id":"W6920571073","doi":"10.6068/dp14ba8756e9c59","title":"Trend 1987 - 2013. Statistics Canada. CANSIM: Labor - Occupations | Country: Canada | Table: Labour force survey estimates (LFS), by National Occupational Classification for Statistics (NOC-S) and sex | Variable: Labour force, Occupations unique to processing, manufacturing and utilities, Females | Units: # Persons x 1,000, 1987-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-143.","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; Census; Official statistics; Wage; Summary statistics; Socioeconomic status; Population statistics; Social statistics; Wages and salaries","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":[0.002274932,0.002290234,0.00278443,0.008862957,0.003777285,0.004946918,0.005279987,0.001405694,0.1078245],"category_scores_gemma":[0.01882373,0.001829051,0.00208167,0.04207112,0.0006225933,0.002562078,0.002379413,0.003125428,0.06563818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05478087,"about_ca_system_score_gemma":0.149082,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9953863,"about_ca_topic_score_gemma":0.9939952,"domain_scores_codex":[0.9955277,0.0003009402,0.0004851533,0.0005500607,0.002063008,0.001073105],"domain_scores_gemma":[0.9650103,0.001189945,0.0009221808,0.0009667387,0.0302803,0.001630523],"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":[0.00002217887,0.000006366253,0.0009488522,0.0002281436,0.0000177457,0.000006138572,0.0000239021,0.00008383918,0.000008095539,0.0003410059,0.9963266,0.001987161],"study_design_scores_gemma":[0.0001508205,0.00001290384,0.02650503,0.0009304041,0.00007025721,0.00002779255,0.0005437414,0.0004199879,0.0001611658,0.000706528,0.970385,0.00008644332],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000588818,0.00005920128,0.00003147069,0.0001355692,0.0000343618,0.00001861993,0.9985032,0.00006793062,0.001090904],"genre_scores_gemma":[0.0008911057,0.0003725381,0.000505076,0.0001956466,0.00002324199,0.000161722,0.9915502,0.0001460473,0.006154405],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1078245,"threshold_uncertainty_score":0.3974649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0538776715779141,"score_gpt":0.3002385502227567,"score_spread":0.2463608786448426,"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."}}