{"id":"W3212785396","doi":"10.2196/30356","title":"Health Information Needs of Young Chinese People Based on an Online Health Community: Topic and Statistical Analysis","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"State Key Laboratory of Networking and Switching Technology","keywords":"Descriptive statistics; The Internet; Cluster analysis; Information needs; Young adult; Medicine; Psychology; Medical education; Computer science; Gerontology; World Wide Web; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005583104,0.0002119365,0.0009059269,0.0005621603,0.0009240952,0.00004034917,0.0002716172,0.0002715437,0.0009394013],"category_scores_gemma":[0.001769057,0.0001650336,0.00007756469,0.00191789,0.0001130405,0.00161072,0.0001680471,0.001722,0.00002968667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002339887,"about_ca_system_score_gemma":0.003050053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001355428,"about_ca_topic_score_gemma":0.002670711,"domain_scores_codex":[0.9921353,0.001869757,0.004369503,0.00006170735,0.001010929,0.00055281],"domain_scores_gemma":[0.9950118,0.001169919,0.001531648,0.0007417531,0.0005092255,0.001035666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001413607,0.0009544806,0.4766443,0.01132688,0.00008854809,4.784416e-7,0.3701271,0.0001280239,1.044341e-7,0.00440008,0.003263997,0.1329246],"study_design_scores_gemma":[0.001536346,0.0004473971,0.6159882,0.0003555676,0.00002018,0.000003100326,0.07463744,0.3015509,3.290477e-7,0.0001373295,0.005167589,0.0001556157],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.899874,0.00002863327,0.09035097,0.005818563,0.000269665,0.0008442439,0.0007798544,0.0001071701,0.001926893],"genre_scores_gemma":[0.923858,0.00009924496,0.009246839,0.06024089,0.00006851713,0.00004803708,0.006400846,0.000008279647,0.00002930438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3014229,"threshold_uncertainty_score":0.9999739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04433345893585678,"score_gpt":0.4688603471652885,"score_spread":0.4245268882294317,"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."}}