{"id":"W3157411108","doi":"10.2196/23898","title":"Health Natural Language Processing: Methodology Development and Applications","year":2021,"lang":"en","type":"editorial","venue":"JMIR Medical Informatics","topic":"Topic Modeling","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Harbin Institute of Technology; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Scope (computer science); Computer science; Health informatics; Data science; Health care; Natural language; Domain (mathematical analysis); Knowledge management; Natural language processing; 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":[0.001223546,0.0002148238,0.0004888631,0.0001170738,0.0001608365,0.0001804359,0.0009784328,0.0005743021,0.00000839846],"category_scores_gemma":[0.0004678835,0.00018312,0.00003676195,0.000233838,0.00007226368,0.0002487667,0.000760208,0.001238823,0.00001345174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000126751,"about_ca_system_score_gemma":0.003839484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000980885,"about_ca_topic_score_gemma":0.00002396146,"domain_scores_codex":[0.99713,0.0001032764,0.0008724784,0.0002432099,0.001286925,0.0003640945],"domain_scores_gemma":[0.9981311,0.0005260913,0.0003912199,0.000462155,0.0001621167,0.0003273032],"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":[5.454875e-7,0.00001545106,4.393131e-7,0.0008115885,0.00001172198,0.000004895455,0.0130555,6.356028e-7,7.946362e-8,0.0006016567,0.2432655,0.742232],"study_design_scores_gemma":[0.0002077121,0.00001274075,0.000001683704,0.0002428129,0.000003147179,0.00002012056,0.0007051564,0.03390048,0.00000501023,0.00006314321,0.9646429,0.0001950511],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000163709,0.003684421,0.850468,0.0007595521,0.1442661,0.0003147533,0.000003615256,0.0001617617,0.0003253649],"genre_scores_gemma":[0.00006814547,0.0001540022,0.7752814,0.00150902,0.2220274,0.0002694397,0.0002625128,0.00001557909,0.0004125173],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7420369,"threshold_uncertainty_score":0.7467418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03536590945122039,"score_gpt":0.377093759670877,"score_spread":0.3417278502196566,"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."}}