{"id":"W2345019564","doi":"10.2196/publichealth.5205","title":"Leveraging Social Media to Promote Public Health Knowledge: Example of Cancer Awareness via Twitter","year":2016,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":140,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; National Institutes of Health","keywords":"Social media; Public health; Internet privacy; Health communication; Computer science; Psychology; Data science; Public relations; Medicine; World Wide Web; Political 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":[0.006379559,0.0002105308,0.000623013,0.0002828518,0.001250704,0.00009376914,0.0003621513,0.0001738369,0.0001516853],"category_scores_gemma":[0.003423036,0.0001796271,0.0000568747,0.001262036,0.0003461448,0.000336361,0.00008243713,0.000187452,0.00002068051],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001210629,"about_ca_system_score_gemma":0.01345466,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02746581,"about_ca_topic_score_gemma":0.04042604,"domain_scores_codex":[0.9947669,0.001578103,0.000787212,0.0005820343,0.0006578895,0.001627892],"domain_scores_gemma":[0.9948532,0.001733796,0.0005002836,0.0002615105,0.0006307267,0.002020461],"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":[0.0000070877,0.00008128667,0.2505816,0.0001948923,0.000007203122,1.261275e-7,0.1783603,1.348127e-8,0.00000674373,0.0007813592,0.004850556,0.5651288],"study_design_scores_gemma":[0.0003668879,0.00005687847,0.3665201,0.0000425881,2.263044e-7,3.627135e-7,0.003227259,0.000003138538,0.000001175627,0.0001921655,0.6294094,0.0001798321],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6593106,0.001546042,0.0007430594,0.33264,0.003542055,0.001785473,0.00003105197,0.0001315663,0.0002701549],"genre_scores_gemma":[0.9914261,0.0009280809,0.0002277032,0.003434886,0.002356641,0.001474338,0.00001760825,0.00003404427,0.0001006273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6245588,"threshold_uncertainty_score":0.9921381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2227714439122429,"score_gpt":0.4407120441209698,"score_spread":0.2179406002087269,"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."}}