{"id":"W2985103099","doi":"10.1093/geroni/igz038.012","title":"ADULT EDUCATION AND TRAINING IN CANADA: OPPORTUNITIES, FUNDING, AND GENDER GAPS","year":2019,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Promotion (chess); Gender gap; Gerontology; Political science; Demographic economics; Economic growth; Psychology; Medicine; Economics","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":[0.006409464,0.0001899966,0.000420574,0.004602152,0.007535767,0.003892054,0.001422471,0.000632227,0.005759793],"category_scores_gemma":[0.01626734,0.0002122669,0.0003326103,0.009496871,0.001633138,0.001140188,0.002533722,0.0008591142,0.0001843221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06825678,"about_ca_system_score_gemma":0.1918688,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9921377,"about_ca_topic_score_gemma":0.9965386,"domain_scores_codex":[0.9932733,0.0005928319,0.0002485688,0.0003579306,0.002443559,0.003083876],"domain_scores_gemma":[0.9811265,0.003291713,0.002517197,0.0002745822,0.006807928,0.005981996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002415034,0.0001784901,0.6631772,0.001704626,0.00009551334,0.0007171263,0.03021208,0.0006131782,0.0004414088,0.03585348,0.03807858,0.2286868],"study_design_scores_gemma":[0.00002206318,0.00005140234,0.8513196,0.002625868,0.00005308615,0.0001378543,0.04837318,0.000591286,0.00021335,0.001776285,0.09478387,0.00005207079],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8205822,0.02378602,0.0009924495,0.04208835,0.0004038919,0.0002198374,0.01169077,0.00007063679,0.1001659],"genre_scores_gemma":[0.9885959,0.004274496,0.0006203977,0.001505312,0.00003310989,0.00005885232,0.0008574595,0.00000992737,0.004044656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06825678,"threshold_uncertainty_score":0.4952399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3151001131715317,"score_gpt":0.4087704979932177,"score_spread":0.09367038482168599,"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."}}