{"id":"W6920412129","doi":"10.6068/dp14ba8f09c5893","title":"Trend 2005 - 2013. Statistics Canada. CANSIM: Labor - Labor Mobility, Turnover and Work Absences | Country: Canada | Table: Labour force survey estimates (LFS), average days lost for personal reasons per full-time employee by North American Industry Classification System (NAICS), sex and age group | Variable: 55 years and over, Total, days lost (including maternity leave), Business, building and other support services, Males | Units: # Days, 2005-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-141.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Economic statistics; Official statistics; Socioeconomic status; Summary statistics; Turnover; Work (physics); Population statistics; Social 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":[0.002394491,0.002524073,0.002995565,0.007897863,0.003052407,0.004341763,0.005564315,0.001476901,0.08316138],"category_scores_gemma":[0.01823684,0.00182762,0.002679907,0.03652032,0.000551676,0.002247919,0.002256652,0.003311944,0.04442196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0499538,"about_ca_system_score_gemma":0.1205136,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9959936,"about_ca_topic_score_gemma":0.9945558,"domain_scores_codex":[0.9959689,0.0002999468,0.0005005183,0.0004702576,0.001768588,0.0009917358],"domain_scores_gemma":[0.9689149,0.00110852,0.001026912,0.0008032918,0.02663033,0.001516076],"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":[0.00003456474,0.000009249144,0.001541188,0.0003394289,0.00003285345,0.000007615027,0.00002866898,0.0001259764,0.000008901136,0.0002947328,0.9955468,0.002030031],"study_design_scores_gemma":[0.0003009159,0.00002620957,0.05423641,0.001628537,0.0001491047,0.00004346164,0.0007790989,0.0007429135,0.0002274985,0.0008023405,0.9409292,0.0001343419],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007633553,0.00007057689,0.00002715861,0.0001242534,0.00003356258,0.00001757691,0.9989254,0.00005637037,0.000668767],"genre_scores_gemma":[0.00112459,0.0003563091,0.0003989055,0.0002024563,0.00002469812,0.0001477715,0.9934434,0.0001033003,0.004198696],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08316138,"threshold_uncertainty_score":0.3624418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02547896399692817,"score_gpt":0.2539684402009338,"score_spread":0.2284894762040057,"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."}}