{"id":"W4389102317","doi":"10.12927/hcq.2023.27221","title":"Intergenerational Civics Programs to Combat Structural Ageism in Canada","year":2023,"lang":"en","type":"article","venue":"Healthcare Quarterly","topic":"Aging and Gerontology Research","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Civics; Public relations; Political science; Sociology; Psychology; Economic growth; Pedagogy; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001123095,0.0001786668,0.0001587873,0.0006684054,0.01035607,0.001675068,0.001314139,0.0005495601,0.008359987],"category_scores_gemma":[0.001870409,0.0001759005,0.0002962261,0.0007115094,0.001019869,0.0004890027,0.003308916,0.001488441,0.0003410304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04553222,"about_ca_system_score_gemma":0.2035714,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9809402,"about_ca_topic_score_gemma":0.9971542,"domain_scores_codex":[0.998812,0.0001397831,0.00001290026,0.00004848694,0.0002003516,0.0007865154],"domain_scores_gemma":[0.9961068,0.00008897794,0.00006501649,0.0000605653,0.0005414067,0.003137191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004644371,0.00403543,0.1887349,0.0003603268,0.00009189004,0.0008862141,0.02159181,0.001122462,0.002481424,0.03761626,0.1469292,0.5956855],"study_design_scores_gemma":[0.000303612,0.0006158204,0.5424999,0.0005439844,0.00008355288,0.0002256434,0.03370155,0.002272369,0.00138393,0.003269268,0.415036,0.00006433847],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8314306,0.002460882,0.001819524,0.02661189,0.0005671937,0.0007013867,0.0006980152,0.0001978576,0.1355126],"genre_scores_gemma":[0.9475614,0.001205252,0.002532991,0.002941847,0.00004265034,0.0001652206,0.0002899045,0.00003376669,0.04522683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04553222,"threshold_uncertainty_score":0.3303609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05821815289850021,"score_gpt":0.3885481307470262,"score_spread":0.330329977848526,"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."}}