{"id":"W4392621496","doi":"10.2196/49608","title":"Advocating for Older Adults in the Age of Social Media: Strategies to Achieve Peak Engagement on Twitter","year":2024,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social media; Gerontology; Psychology; Social engagement; Internet privacy; Sociology; Media studies; Computer science; Medicine; World Wide Web; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001088895,0.0001044722,0.0001322521,0.0001780043,0.0002567234,0.0001093663,0.0003795686,0.00008781072,0.00002128403],"category_scores_gemma":[0.0001710868,0.00008160854,0.00006361635,0.0004235645,0.000115386,0.0001309794,0.00005794532,0.0002900886,0.00001251081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000722584,"about_ca_system_score_gemma":0.00008851031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000178257,"about_ca_topic_score_gemma":0.002282708,"domain_scores_codex":[0.9987558,0.000161396,0.0002023666,0.0002563283,0.0003010425,0.0003230718],"domain_scores_gemma":[0.9991222,0.0006545019,0.00003977487,0.0001309308,0.00003244478,0.00002016705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002143188,0.00006283231,0.0002103882,0.000124099,0.00001501759,0.00001983128,0.9277965,0.00000761611,0.0002119098,0.03345024,0.004754306,0.0333258],"study_design_scores_gemma":[0.0007694407,0.0001265343,0.07768072,0.001011601,0.00002467329,7.721614e-7,0.875567,0.0000796174,0.0003201828,0.008222043,0.03586629,0.0003311617],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9684572,0.00006331695,0.0003520039,0.0214036,0.0003375468,0.001216085,0.000006915188,0.0001984639,0.007964846],"genre_scores_gemma":[0.9984194,0.000003359663,0.0002948943,0.0004815835,0.0003042559,0.0003921941,0.000005459417,0.00001435536,0.00008451685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07747033,"threshold_uncertainty_score":0.33279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03176150763450605,"score_gpt":0.350473158907505,"score_spread":0.318711651272999,"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."}}