{"id":"W2002519110","doi":"10.7202/050582ar","title":"Retirement and Skill Issues in Northern Ontario Industries","year":2005,"lang":"en","type":"article","venue":"Relations industrielles","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Relation (database); Health and Retirement Study; Business; Retirement age; Gerontology; Demographic economics; Psychology; Labour economics; Economics; Medicine; Finance; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0004627163,0.0001031236,0.0001697078,0.001486515,0.005086773,0.001063309,0.0003451482,0.0003308488,0.003987346],"category_scores_gemma":[0.001730762,0.0001990493,0.0001673278,0.001979174,0.0008105167,0.0004226658,0.001096238,0.0003670214,0.0002682922],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01775496,"about_ca_system_score_gemma":0.0183868,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9674928,"about_ca_topic_score_gemma":0.9928638,"domain_scores_codex":[0.999513,0.0000478991,0.00002363849,0.00003367321,0.0001447094,0.0002370423],"domain_scores_gemma":[0.9987286,0.0001065616,0.0002981169,0.00003072393,0.0003122707,0.0005237515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001053203,0.0001345386,0.9153711,0.00007204644,0.00001232589,0.0006466648,0.0548743,0.0001225082,0.0004287516,0.001023115,0.002835817,0.02437358],"study_design_scores_gemma":[0.000002684472,0.00002501259,0.9774979,0.0000301423,0.000002344669,0.00004668847,0.01677156,0.0000325788,0.00002118718,0.00006493511,0.005500617,0.000004355234],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912005,0.0005017282,0.00001962576,0.0005299311,0.000008186594,0.00001610571,0.0003126081,0.000002077228,0.007409209],"genre_scores_gemma":[0.9891363,0.0009293328,0.00006271857,0.0001680384,0.000009852699,0.00002028402,0.0002729665,0.000002560259,0.009397896],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.982245,"threshold_uncertainty_score":0.1288218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1422992345392359,"score_gpt":0.3756988324953141,"score_spread":0.2333995979560782,"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."}}