{"id":"W1965562398","doi":"10.1177/1932296815572680","title":"Reimbursement Programs and Health Technology Assessment for Diabetes Devices and Supplies","year":2015,"lang":"en","type":"article","venue":"Journal of Diabetes Science and Technology","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reimbursement; Health technology; Business; Advisory committee; Medicine; Process (computing); Health care; Computer science; Public administration; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02005956,0.000435467,0.0005187839,0.006454906,0.001506491,0.004824116,0.001148211,0.001561681,0.00419041],"category_scores_gemma":[0.09697108,0.0004299843,0.001056645,0.008676097,0.001697461,0.001924192,0.001509668,0.00200966,0.0003979313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04961628,"about_ca_system_score_gemma":0.07566099,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7159204,"about_ca_topic_score_gemma":0.7329019,"domain_scores_codex":[0.9655018,0.01099926,0.001795052,0.000802252,0.01826318,0.002638468],"domain_scores_gemma":[0.9444093,0.02372645,0.005585922,0.001242929,0.02239382,0.002641518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003588002,0.00030363,0.1161592,0.002462496,0.0003939244,0.0001813344,0.001840081,0.009840117,0.0004304067,0.1943864,0.1375549,0.5360886],"study_design_scores_gemma":[0.0003667299,0.0003290429,0.4062591,0.00686223,0.0005130033,0.0002416913,0.001667407,0.01186372,0.0008624185,0.03088478,0.5399342,0.0002157031],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1387741,0.1057186,0.05621211,0.1789341,0.001666387,0.004408248,0.02480043,0.0005797982,0.4889063],"genre_scores_gemma":[0.845371,0.06702833,0.0413467,0.01148976,0.0008472841,0.001381909,0.01120753,0.0001091032,0.02121839],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7159204,"threshold_uncertainty_score":0.5715051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2833148874188977,"score_gpt":0.4500558630950076,"score_spread":0.16674097567611,"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."}}