Bibliographic record
Abstract
Note: Figures and Tables are indicated by italic page numbers; abbreviations: DM = diabetes mellitus, IFG = impaired fasting glycemia, IGT = impaired glucose tolerance, T1D = type 1 diabetes, T2D = type 2 diabetes abdominal adiposity see central obesity abdominal aortic aneurysm(AAA), 550-7 definition(s), 550, 556 prevalence, 550, 551-5 risk factors, 551-5, 556 Aboriginal people (Canada), 255 diabetes prevalence, 256, 641 see also First Nations people acanthosis nigricans, 22, 23, 347, 397 acarbose, 450, 455-6 accelerometers, 74 ACE gene, 507, 508 ACE inhibitors see angiotensin-converting enzyme inhibitors acromegaly, 16, 22 ACT NOW study, 454-5 activity monitors, 74-5 acute complications of diabetes, 577-602 in Africa, 143 in North America, 249 see also diabetic ketoacidosis; hyperglycemic hyperosmolar state; hypoglycemia Addison's disease, 20, 592 adenovirus, diabetes associated with, 22 adipocyte function, HAART action on, 671-2 adiponectin, 190 HIV-infected patients, 670-1 adiposity measures see body mass index (BMI); waist circumference; waist:hip ratio (WHR) adult-onset diabetes see type 2 diabetes Adult Treatment Panel see National Cholesterol Education Program Adult Treatment Panel III advanced glycation end-products (AGEs), 569 Aerobic Center Longitudinal Study (ACLS), 39 Africa childhood diabetes, 386-7 complications due to diabetes, 143-4 costs of diabetes care, 144 diabetes prevalence, 113, 133, 134-40, 143 age variationsy, 140, 142 ethnic differences, 139 migration effects, 139-40 proportion with known diabetes, 140, 141, 142 urban-rural differences, 139 gender distribution, 140 health expenditure for diabetes, 630, 631 IGT prevalence, 113, 136, 137, 138, 298 incidence of type 1 diabetes, 357, 358 obesity prevalence, 58, 64 population, 134 African Americans, 295-322 childhood diabetes, 307-8, 388, 389, 390 clinical variants of diabetes, 295, 304-8 atypical diabetes of childhood, 307 β-cell function preservation, 306 β-cell function recovery, 305-6 diabetic ketoacidosis with type 2 diabetes, 306-7 remission in diabetes, 304-5 type 1 diabetes among children, 307-8 complications due to diabetes, 308-13 amputations, 312 cardiovascular disease, 312-13 end-stage renal disease, 308-10 nephropathy, 310-12 peripheral vascular disease, 312 retinopathy, 308, 479 diabetes prevalence, 140, 296-7 children and adolescents, 340 HIV-infected, 667 metabolic insulin resistance syndrome, 300-2 mortality from diabetes, 313 overweight prevalence, children and adolescents, 346 type 1 diabetes, incidence among children, 307 type 2 diabetes in children and adolescents, 340 clinical variants, 295, 304-8 pathogenesis, 295, 303-4 prevalence, 296-7 risk factors, 297-300 Afro-Caribbeans in Caribbean region demographics, 164 diabetes prevalence, 165 hypertension among, 165 IGT prevalence, 165 retinopathy, 308 in UK cardiovascular disease, 312 metabolic syndrome, 47 age profile of population, effect on diabetes prevalence, 113-14, 207 age variations African Americans, 297 BMI, 62, 63 diabetes prevalence, in South East Asia, 212 incidence of type 1 diabetes, 361-2 life expectancy reduction, 612, 613 obesity-diabetes association, 59-60 AGREE (Appraisal of Guidelines Research and Evaluation) Collaboration, 642 guideline development tools, 642, 643 Alaska Natives, 255 diabetes prevalence, 256 children and adolescents, 340 see also Native Americans Albania, 114 albumin:creatinine ratio (ACR), for microalbuminuria, 500 albuminuria, 127, 501, 504-5 insulin resistance and, 503-4 vascular disease and, 503 see also microalbuminuria 677
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.882 | 0.852 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".