{"id":"W3013607005","doi":"10.2196/17813","title":"Determining the Topic Evolution and Sentiment Polarity for Albinism in a Chinese Online Health Community: Machine Learning and Social Network Analysis","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"melanin and skin pigmentation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities","keywords":"Albinism; Social media; Sentiment analysis; Data science; Computer science; Psychology; World Wide Web; Artificial intelligence; Internet privacy; Medicine; Natural language processing; Biology; Genetics","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":[0.0004567901,0.0000690001,0.0001425177,0.00001993092,0.0002169486,0.00001986946,0.00006334005,0.00007887441,0.000003552272],"category_scores_gemma":[0.00008616213,0.00005003094,0.00003273162,0.0001038702,0.0000463094,0.000005553055,0.0001095584,0.0002227758,1.354006e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001108173,"about_ca_system_score_gemma":0.00003180554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003077606,"about_ca_topic_score_gemma":0.0002558698,"domain_scores_codex":[0.9993159,0.0001291989,0.0002625301,0.00005085386,0.0001202994,0.0001211946],"domain_scores_gemma":[0.9997193,0.00004205228,0.0001015235,0.00004851794,0.00001612301,0.00007248418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001419499,0.0001926557,0.9115661,0.0005817394,0.0003545614,8.256661e-7,0.04344257,0.0001517,0.0002537244,0.0002720041,0.000701403,0.04234074],"study_design_scores_gemma":[0.003984813,0.0009496572,0.470555,0.00004086983,0.0001144576,0.000006849285,0.008124298,0.5076933,0.00002636921,0.0002066993,0.008020264,0.0002774321],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895242,0.0001305004,0.008096807,0.001994321,0.00002008647,0.000196967,0.00001224124,0.000005295908,0.00001956157],"genre_scores_gemma":[0.9954561,0.00007303477,0.001024597,0.002659419,0.0001264327,0.000009735185,0.0006402183,0.0000034255,0.000007030596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5075416,"threshold_uncertainty_score":0.2040202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01724818146850506,"score_gpt":0.3303326855509111,"score_spread":0.3130845040824061,"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."}}