{"id":"W6958341759","doi":"10.6068/dp15b879a836632","title":"Trend 1997 - 2013. Statistics Canada. CANSIM: Labor - Industries | Country: Canada | 240_1_1: Labour force survey estimates (LFS), employees by establishment size, North American Industry Classification System (NAICS), sex and age group | 240_0_1: 15 to 24 years, Less than 20 employees, Finance, insurance, real estate and leasing, Both sexes | 240_0_2: # Persons x 1,000, 1997-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-139.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"Plant pathogens and resistance mechanisms","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Economic statistics; Official statistics; Summary statistics; Wages and salaries; Socioeconomic status; Real estate; Population 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":[0.002069004,0.002352039,0.002945357,0.008251606,0.003349574,0.004666425,0.005150213,0.001482731,0.0943206],"category_scores_gemma":[0.01645342,0.001760537,0.002051646,0.04110843,0.0005711393,0.002294621,0.002402503,0.003048759,0.06241951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04302101,"about_ca_system_score_gemma":0.1169837,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944192,"about_ca_topic_score_gemma":0.99264,"domain_scores_codex":[0.9961557,0.0002592445,0.0004343752,0.0005104004,0.001620507,0.001019835],"domain_scores_gemma":[0.9715479,0.001100071,0.0008347352,0.0009061812,0.02413346,0.001477622],"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":[0.0000243548,0.00000608082,0.0009274576,0.0002299734,0.00001918358,0.000006322625,0.00002412461,0.00008073779,0.000008174114,0.0002981357,0.9966775,0.001697974],"study_design_scores_gemma":[0.0001754973,0.00001409198,0.02709818,0.0009522692,0.00007667786,0.00002777779,0.0006113481,0.0004082775,0.0001678148,0.0006457025,0.9697337,0.00008867532],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005488291,0.00004794438,0.00002223635,0.0001033728,0.00002863537,0.00001235324,0.998982,0.00005357567,0.0006949806],"genre_scores_gemma":[0.0006723407,0.0002535699,0.0002800666,0.0001393028,0.0000170596,0.000108807,0.9944593,0.00009376576,0.003975855],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0943206,"threshold_uncertainty_score":0.3155338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02576524266501113,"score_gpt":0.2297951778608344,"score_spread":0.2040299351958232,"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."}}