{"id":"W4415846069","doi":"10.1186/s12877-025-06501-8","title":"Developing an evidence base to inform retirement home policy development using an equity and diversity lens: a mixed methods study protocol","year":2025,"lang":"en","type":"article","venue":"BMC Geriatrics","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advantage Forensics (Canada); University of Toronto; Ontario Tech University; Toronto and Region Conservation Authority; Institut du Savoir Montfort; Ottawa Hospital; Bruyère; University of Ottawa","funders":"Canadian Institutes of Health Research","keywords":"Equity (law); Leverage (statistics); Dissemination; Protocol (science); Health equity; Work (physics); Health care; Diversity (politics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01424214,0.0002151946,0.0003324219,0.001085086,0.001133064,0.000596513,0.0007821767,0.00008345127,0.000009162574],"category_scores_gemma":[0.003496853,0.0001826242,0.000046669,0.003360423,0.00003564175,0.001058612,0.002947135,0.0001041304,0.000005570623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003328681,"about_ca_system_score_gemma":0.0012377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006434001,"about_ca_topic_score_gemma":0.001069359,"domain_scores_codex":[0.9959297,0.0007257722,0.0009019968,0.0007256352,0.001350518,0.0003663716],"domain_scores_gemma":[0.9976504,0.0005667837,0.0002831344,0.0006149916,0.0006849776,0.000199687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005813628,0.0005998714,0.3314073,0.0002292929,0.0000435932,0.000006260902,0.02077398,0.003279225,0.0004855398,0.002679545,0.0001110441,0.6398029],"study_design_scores_gemma":[0.002199485,0.0007527702,0.8952675,0.0002276393,0.0001027269,0.000003693161,0.02497598,0.05244834,0.0006171559,0.01960193,0.002791822,0.001010903],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5827067,0.000008727357,0.402541,0.0001317168,0.0001398371,0.01435555,0.00000163818,0.00004870384,0.00006613963],"genre_scores_gemma":[0.4037308,0.000003944795,0.5922939,0.000392401,0.00004263559,0.003469509,0.000001627152,0.000008785732,0.00005645489],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.638792,"threshold_uncertainty_score":0.8714727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5812083239209116,"score_gpt":0.566642717633189,"score_spread":0.01456560628772263,"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."}}