{"id":"W2659087430","doi":"10.14236/jhi.v24i2.900","title":"Designing Health Information Technology Tools to Prevent Gaps in Public Health Insurance","year":2017,"lang":"en","type":"article","venue":"Journal of Innovation in Health Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Golder Associates (Canada)","funders":"Patient-Centered Outcomes Research Institute","keywords":"Public health insurance; Business; Health information technology; Public health; Health insurance; Health informatics; Actuarial science; Internet privacy; Medicine; Computer science; Health care; Nursing; Economic growth; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02016664,0.001054409,0.000405848,0.003583567,0.002136712,0.006151278,0.002702295,0.0019565,0.002891829],"category_scores_gemma":[0.04798356,0.0008945926,0.0008600672,0.002014508,0.001979556,0.007880818,0.003697667,0.001422607,0.0007269582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003116549,"about_ca_system_score_gemma":0.01085232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003399198,"about_ca_topic_score_gemma":0.003350369,"domain_scores_codex":[0.9904099,0.005792613,0.0009263219,0.0007799247,0.001047301,0.001044028],"domain_scores_gemma":[0.9535547,0.03502756,0.002731347,0.00282838,0.004335437,0.001522491],"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":[0.0005728012,0.003391019,0.0851115,0.006137974,0.0002414074,0.003535948,0.1061914,0.01885457,0.02005937,0.04747213,0.02699904,0.6814329],"study_design_scores_gemma":[0.0009661813,0.003699729,0.04986127,0.01026026,0.001010289,0.00285911,0.1896984,0.1335767,0.04975694,0.1140499,0.4438289,0.0004324149],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4622565,0.001429916,0.4691206,0.01295402,0.0003038992,0.006801709,0.0008249642,0.008621102,0.03768729],"genre_scores_gemma":[0.4007951,0.0007226233,0.5920343,0.0008286232,0.00003425826,0.002174322,0.0008614116,0.0002695127,0.002279948],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02016664,"threshold_uncertainty_score":0.1066527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1411957874474565,"score_gpt":0.4608994983753993,"score_spread":0.3197037109279429,"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."}}