{"id":"W6976227080","doi":"10.6068/dp14ba8c8f4234","title":"Trend 1987 - 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: 25 to 44 years, Other personal (including maternity leave), Construction, Both sexes | Units: # Days, 1987-2013. 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; Official statistics; Economic statistics; Summary statistics; Socioeconomic status; Work (physics); Turnover; 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":[0.002428667,0.002554345,0.003057285,0.00894352,0.003104182,0.004522705,0.005645326,0.00151213,0.08946495],"category_scores_gemma":[0.01918433,0.001849414,0.002559394,0.04000958,0.0005851787,0.002369377,0.002427972,0.003326953,0.05307731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04870142,"about_ca_system_score_gemma":0.1228725,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9952991,"about_ca_topic_score_gemma":0.9939299,"domain_scores_codex":[0.9955941,0.0003191,0.0005153355,0.0005297934,0.001975057,0.001066709],"domain_scores_gemma":[0.9659174,0.001278636,0.001182656,0.0009493314,0.02902074,0.001651159],"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":[0.00003056213,0.00000918871,0.001364147,0.0002898609,0.00002850307,0.000006316242,0.00002672526,0.0001219569,0.00000783056,0.0002806491,0.9960969,0.001737456],"study_design_scores_gemma":[0.0002876124,0.00002272734,0.04680724,0.001228038,0.000117667,0.00003466216,0.0006343726,0.0006786168,0.0001939245,0.0007159017,0.9491637,0.0001155423],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006565531,0.00005113845,0.00002464407,0.00009470824,0.00002517417,0.00001630701,0.9990383,0.00005668582,0.0006273666],"genre_scores_gemma":[0.0008433872,0.0002548966,0.0003175754,0.0001421628,0.00001985102,0.0001361152,0.9945315,0.00009734889,0.00365707],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08946495,"threshold_uncertainty_score":0.3533552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0269180842567196,"score_gpt":0.2522061433189739,"score_spread":0.2252880590622543,"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."}}