{"id":"W3083506895","doi":"10.2196/20558","title":"Factors Associated With Influential Health-Promoting Messages on Social Media: Content Analysis of Sina Weibo","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Chongqing Medical University","keywords":"Social media; Health communication; Content analysis; Descriptive statistics; Health information; Logistic regression; Psychology; Coding (social sciences); Internet privacy; Computer science; World Wide Web; Health care; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.002558902,0.0004976672,0.0004110326,0.007562088,0.001002444,0.001585499,0.000298206,0.0003806413,0.001539278],"category_scores_gemma":[0.01516018,0.0001802762,0.0007119557,0.00688651,0.0006430323,0.001379467,0.0008790654,0.000471547,0.000296223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00113503,"about_ca_system_score_gemma":0.001046767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009269774,"about_ca_topic_score_gemma":0.008735576,"domain_scores_codex":[0.9986999,0.0004486101,0.000171873,0.0001614613,0.0003843175,0.0001338224],"domain_scores_gemma":[0.97591,0.01746127,0.003217657,0.0004323111,0.002484611,0.0004941943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002486998,0.000161576,0.9166973,0.0007596516,0.0001440438,0.0005615906,0.02744075,0.0004071434,0.001872861,0.0005818222,0.001571327,0.04955325],"study_design_scores_gemma":[0.000006235375,0.0000854849,0.9696674,0.0001697502,0.0001357629,0.0002199121,0.01909914,0.005178569,0.0008466872,0.0002755704,0.0042711,0.00004442221],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936771,0.0002994538,0.001041532,0.0001545703,0.00001629656,0.0002683327,0.001907928,0.00004103313,0.002593673],"genre_scores_gemma":[0.9934401,0.0003142492,0.003025086,0.00004094912,0.00003315456,0.0004499868,0.001800116,0.00002728669,0.0008691143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009269774,"threshold_uncertainty_score":0.01843166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2116691781119865,"score_gpt":0.4618805703017906,"score_spread":0.2502113921898041,"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."}}