{"id":"W6976510170","doi":"10.6068/dp14ba86baa7855","title":"Trend 1997 - 2013. Statistics Canada. CANSIM: Labor - Commuting to Work | Country: Canada | Table: Labour force survey estimates (LFS), employees by union coverage, North American Industry Classification System (NAICS), sex and age group | Variable: 15 years and over, Transportation and warehousing, Males, No union coverage | Units: # Persons x 1,000, 1997-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-135.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Health, Education, and Cultural Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Residence; Official statistics; Economic statistics; Work (physics); Summary statistics; Socioeconomic status; General Social Survey; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001075582,0.0004850903,0.0007407464,0.00006012788,0.0007952474,0.0004154413,0.0005922398,0.0003623722,0.0001061465],"category_scores_gemma":[0.0001239711,0.0004859099,2.120817e-7,0.0006229545,0.0003764763,0.0003231798,0.00008961419,0.000634356,0.000001856277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004056527,"about_ca_system_score_gemma":0.004536063,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.999891,"about_ca_topic_score_gemma":0.9999167,"domain_scores_codex":[0.9961351,0.001013776,0.0005869018,0.0008460999,0.0007807004,0.0006374309],"domain_scores_gemma":[0.9971218,0.0007977327,0.0006410212,0.0006932644,0.0001097949,0.0006364402],"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":[0.00003084893,0.00003328894,0.01021922,0.000513531,0.000106938,0.00002815105,0.0001784592,0.000007737092,2.728902e-7,0.0002312127,0.9883718,0.0002784814],"study_design_scores_gemma":[0.0003060485,0.00006871401,0.007860755,0.0001092873,0.00015217,0.000005597587,0.004824894,0.00008871176,2.494384e-9,9.579443e-8,0.9860294,0.0005543155],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007380281,0.001794964,0.00001343215,0.00001658675,0.0004116175,0.0006697046,0.9960471,0.00007114033,0.0002374209],"genre_scores_gemma":[0.00300795,0.004917958,0.0001023022,0.0002001284,0.0001662865,0.00001670781,0.9896469,0.00009631862,0.001845516],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.006400272,"threshold_uncertainty_score":0.9997593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02934249307556167,"score_gpt":0.2738465590548827,"score_spread":0.244504065979321,"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."}}