{"id":"W4408568351","doi":"10.18438/eblip30730","title":"Evidence Summary Theme: Equity, Diversity, and Inclusion","year":2025,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Equity (law); Theme (computing); Diversity (politics); Inclusion (mineral); Computer science; World Wide Web; Data science; Sociology; Political science; Social science; Law; Anthropology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.07742988,0.00175272,0.006948358,0.01006645,0.002261832,0.01454183,0.004675146,0.01243529,0.03006606],"category_scores_gemma":[0.3451635,0.001384228,0.007354409,0.009521644,0.00373371,0.01048235,0.01038255,0.01334862,0.004603656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01024521,"about_ca_system_score_gemma":0.02750807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004183901,"about_ca_topic_score_gemma":0.006112014,"domain_scores_codex":[0.8969649,0.04172564,0.02998455,0.004779448,0.02466011,0.001885227],"domain_scores_gemma":[0.716608,0.1987445,0.03523934,0.005436207,0.03958568,0.004386242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003768735,0.00006765081,0.0009697895,0.4581161,0.002019832,0.0001139522,0.0007860984,0.000190735,0.0001766676,0.02090045,0.2428965,0.2733854],"study_design_scores_gemma":[0.0002816179,0.0001061249,0.00175111,0.7163565,0.002352647,0.0001971846,0.0005443132,0.0001082024,0.0001646028,0.009794243,0.2683013,0.00004209636],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.0006137801,0.7642928,0.00279149,0.173547,0.03357182,0.003339103,0.004529308,0.00009574225,0.01721892],"genre_scores_gemma":[0.01566126,0.8441141,0.01214603,0.09444457,0.0176503,0.008523257,0.003210459,0.0001093726,0.004140597],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07742988,"threshold_uncertainty_score":0.4094933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06342791963643436,"score_gpt":0.4174719262694627,"score_spread":0.3540440066330283,"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."}}