{"id":"W4407911622","doi":"10.2196/68093","title":"Using Social Media to Engage and Enroll Underrepresented Populations: Longitudinal Digital Health Research","year":2025,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Social media; Psychology; Medical education; Sociology; Medicine; Computer science; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02853188,0.0003832054,0.0003796908,0.002998256,0.003572843,0.002445136,0.0008479216,0.00106071,0.002915725],"category_scores_gemma":[0.03040974,0.0005441036,0.0008447651,0.00287122,0.001570607,0.004360514,0.003719089,0.001435261,0.000935005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001777294,"about_ca_system_score_gemma":0.00438896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008636132,"about_ca_topic_score_gemma":0.0154902,"domain_scores_codex":[0.9888256,0.007021056,0.0009430851,0.0009094483,0.001282803,0.001017937],"domain_scores_gemma":[0.984054,0.005289016,0.004238875,0.002249725,0.002911447,0.001256968],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000478077,0.004113191,0.9187409,0.0005087114,0.000270128,0.0002332476,0.01829295,0.0001269269,0.0005708474,0.001417282,0.002717811,0.05252989],"study_design_scores_gemma":[0.0006623933,0.009246134,0.8781567,0.002527931,0.000760146,0.0008324676,0.07920496,0.001850613,0.002574088,0.004952796,0.0190897,0.0001420875],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875987,0.0009363562,0.003029853,0.001211466,0.00006027254,0.003449512,0.001054424,0.00002465805,0.002634756],"genre_scores_gemma":[0.9778438,0.001209877,0.008130952,0.00167373,0.00008134363,0.009012717,0.001085789,0.0000180946,0.0009437796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9714682,"threshold_uncertainty_score":0.1508928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7408214358071563,"score_gpt":0.6607968642167372,"score_spread":0.08002457159041909,"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."}}