The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index; 1 of the 6 sources its claims cite were checked for support.
Homeostasis model assessment: insulin resistance and ?-cell function from fasting plasma glucose and insulin concentrations in man
Open accessAbstract
The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
15 Own result · 7 Own interpretation · 3 No full text of the sources · 1 Partly supported · 1 No basis given · accuracy not yet measured
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“The fasting plasma insulin concentration is largely determined by the glucose concentration [3]”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
What the sources say
- Partly supportedcites [3] McCarthy ST, Harris F, Turner RC (1977) Glucose control of basal insulin secretion in diabetes. Diabetologia 13: 93?97 sourceExperimental — accuracy not yet measured
The Results and Discussion (page unavailable in our copy) show that changing plasma glucose affects basal insulin secretion. But they also report markedly impaired responses in diabetic subjects, including cases where insulin remained nearly constant despite a substantial glucose decrease. The paper therefore supports glucose as an influence, but not the unqualified claim that it largely determines fasting insulin concentration. (LLM, conf=0.84)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The estimate of deficient/3cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (R~ = 0.61, p< 0.01)”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (R~=0.88,p<0.0001)”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There was no correlation with any aspect of insulin-receptor binding.”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the fasting insulin concentration (P~ = 0.81, p < 0.0001)”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The mean coefficient of variation over the two studies was 32%.”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Reproducibility of estimate of /3-cell function by HOMA
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“in both groups together (1% 0.61, p < 0.01 : Fig. 3).”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Comparisons of methods of assessing ~3-cell function
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and with the estimate from the intravenous glucose tolerance test (R~ = 0.64, p < 0.05).”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and in both groups together: 1% = 0.64, p< 0.05; Fig. 3).”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > HOMA compared with intravenous glucose tolerance test.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Neither receptor numbers or any aspect of high or low affinity binding correlated with other measures of insulin resistance (HOMA, clamp, basal insulin or CIGMA: ~ all < 0.55; NS).”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > HOMA compared with the hyperglycaemic clamp. The
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
- It may state two separate claims as one. 2
- The quote only partly states this claim. 1
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for/3-cell deficit) limits its use”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Summary.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The mean coefficient of variation over the two studies was 31%.”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Hyperglycaemic clamp : ~-cell function (%)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The degree of the hyperglycaemia does not correlate significantly with either the degrees of abnormal fl-cell function or insulin resistance.”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
- Rests on an assumption: The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
The authors state this as an assumption.
Normal-weight normal subjects aged <35 years have 100% beta-cell function and an insulin resistance of 1.
“Assuming that normal-weight normal subjects aged < 35 years have 100% r-cell function, and an insulin resistance of 1, the values for a patient can be assessed from the insulin and glucose concentrations by the formulae: r-cell”
The paper relies on this without support.
The plasma glucose:insulin response for normal subjects is equivalent to the C-peptide response and is insulin = 5 (glucose-3.5).
“The plasma glucose:insulin response for normal subjects, equivalent to the C-peptide response, is insulin = 5 (glucose-3.5).”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“After the unprocessed diet, fasting glucose and insulin levels tended to decrease compared to baseline and the homeostasis model assessment of insulin resistance (HOMA-IR) (Matthews et al., 1985) was significantly decreased compared to baseline.”
From Ultra-Processed Diets Cause Excess Calorie Intake and Weight Gain: An Inpatient Randomized Controlled Trial of Ad Libitum Food Intake (2019) · cites this paper as Matthews et al., 1985
The cited source says what the claim attributes to it.
In the citing paper
“The Homeostasis Model Assessment of Insulin Resistance (HoMA-IR) was calculated according to Matthews et al. [25].”
From Chronotype: A Tool to Screen Eating Habits in Polycystic Ovary Syndrome? (2022) · cites this paper as [25]
The cited source says what the claim attributes to it.
In the citing paper
“AAV9-mTERT treated mice also showed a trend for an improved glucose uptake and a better homeostatic model assessment (HOMA (Heikkinen et al, 2007; Matthews et al, 1985)) compared to the AAV9-eGFP controls, although differences did not reach statistical significance (Supporting Information Fig S4D and E).”
From Telomerase gene therapy in adult and old mice delays aging and increases longevity without increasing cancer (2012) · cites this paper as Matthews et al, 1985
In the citing paper
“Surrogate markers of peripheral insulin activity, such as homeostasis model assessment and whole-body insulin sensitivity indexes, could be useful as well in the early identification of patients with IR, before overt DM sets in ().”
From Glucose Metabolism Abnormalities in Cushing Syndrome: From Molecular Basis to Clinical Management (2017) · cites this paper as [240]
In the citing paper
“ndirect estimates of insulin resistance, such as HOMA-IR 63 and QUICKI, 64 are derived from fasting S-insulin and glucose concentrations and have been widely used in both nondiabetic and type 2 diabetic subjects as surrogates of insulin sensitivity.65,66”
From Increased liver fat, impaired insulin clearance, and hepatic and adipose tissue insulin resistance in type 2 diabetes. (2008) · cites this paper as [63]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > Subjects and procedures
“The same 12 normal subjects and 11 Type 2 diabetic patients came to the hospital fasting on a separate day for a continuous infusion”
§ Homeostasis model assessment: insulin resistance and fl-cell function from fasting plasma glucose and insulin concentrations in man > HOMA compared with the hyperglycaemic clamp. The
“HOMA compared with CIGMA.The HOMA estimate of insulin resistance from the mean of 15 stressed fasting samples before the CIGMA correlated with that measured by CIGMA in 11 normal subjects (R~ = 0.69, p < 0.02), in 12 diabetic subjects (R~ 0.97, p < 0.0001)”
Citations
Cites
Glucose clamp technique: a method for quantifying insulin secretion and resistance.
DeFronzo, R. A., Tobin, J. D., & Andres, R. (1979) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.1979.237.3.e214 · Cited by 7,425
Quantitative estimation of insulin sensitivity.
Bergman, R. N., Ider, Y. Z., Bowden, C. R., & Cobelli, C. (1979) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.1979.236.6.e667 · Cited by 1,874 · cited 1×
“This use of modelling to provide a reference graph contrasts with other models where an individual patient's data have to be entered into a computer to determine the relationships between rapidly changing variables, such as occur after an intravenous glucose test [19].”
Method[WHO Expert Committee on diabetes mellitus].
Reitsma, W. D., & Terpstra, J. (1981) · PubMed · Cited by 556
Turner, R. C., Holman, R. R., Matthews, D., Hockaday, T. D. R., & Peto, J. (1979) · Metabolism · doi:10.1016/0026-0495(79)90146-x · Cited by 388
Self-citationCharacteristics of Human Erythrocyte Insulin Receptors
Gambhir, K. K., Archer, J. A., & BRADLEY, C. J. (1978) · Diabetes · doi:10.2337/diab.27.7.701 · Cited by 290
The Insulin Receptor: Its Role in Insulin Resistance of Obesity and Diabetes
Olefsky, J. M. (1976) · Diabetes · doi:10.2337/diab.25.12.1154 · Cited by 289
Hosker, J. P., Matthews, D. R., Rudenski, A. S., Burnett, M. A., Darling, P., Bown, E. G., & Turner, R. C. (1985) · Diabetologia · doi:10.1007/bf00280882 · Cited by 287
Self-citationPulsatile Insulin Has Greater Hypoglycemic Effect Than Continuous Delivery
Matthews, D. R., Naylor, B. A., Jones, R., Ward, G. M., & Turner, R. C. (1983) · Diabetes · doi:10.2337/diab.32.7.617 · Cited by 256
Self-citationControl of pulsatile insulin secretion in man
Matthews, D. R., Lang, D. A., Burnett, M. A., & Turner, R. C. (1983) · Diabetologia · doi:10.1007/bf00282705 · Cited by 175
Self-citationTHE BASAL PLASMA GLUCOSE: A SIMPLE RELEVANT INDEX OF MATURITY‐ONSET DIABETES
HOLMAN, R. R., & TURNER, R. C. (1981) · Clinical Endocrinology · doi:10.1111/j.1365-2265.1981.tb00196.x · Cited by 64
Self-citation
Research works printed but not linked: 2
- Metropolitan Life Assurance Co (1959) Net weight standard for men and women. Stat Bull Metrol Life Found 40: 1?4
- Matthews DR, Hosker JP (1984) An unbiased, flexible computer programme for glucose clamping, with graphics and running statistics. Diabetologia 27: 308?309 A
Cited by
Sorted by citations
Items 7,901–8,000 of 31,469
Decreased renal function in overweight and obese prepubertal children
Correia‐Costa, L., Afonso, A. C., Schaefer, F. S., Guimarães, J. T., Bustorff, M., Guerra, A., Barros, H., & Azevedo, A. (2015) · Pediatric Research · doi:10.1038/pr.2015.130 · Cited by 46
Depressive Symptom Clusters as Predictors of 6-Year Increases in Insulin Resistance
Khambaty, T., Stewart, J. C., Muldoon, M. F., & Kamarck, T. W. (2014) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000063 · Cited by 49
Viazzi, F. C., Rebora, P., Giussani, M., Orlando, A., Stella, A., Antolini, L., Valsecchi, M. G., Pontremoli, R., & Genovesi, S. (2016) · Hypertension · doi:10.1161/hypertensionaha.115.06852 · Cited by 46
Romain, C., Gaillet, S., Carillon, J., Vidé, J., Ramos, J., Izard, J., Cristol, J., & Rouanet, J. (2012) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf303549t · Cited by 48
Metabolomic profiling to dissect the role of visceral fat in cardiometabolic health
Menni, C., Migaud, M. E., Glastonbury, C. A., Beaumont, M., Nikolaou, A. I., Small, K. S., Brosnan, M. J., Mohney, R. P., Spector, T. D., & Valdes, A. M. (2016) · Obesity · doi:10.1002/oby.21488 · Cited by 45
Park, H., Hur, H. J., Kim, S., Park, S., Hong, M. J., Sung, M. J., Kwon, D. Y., & Kim, M. (2016) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201500689 · Cited by 46
Gurley, J. M., Griesel, B. A., & Olson, A. L. (2016) · Diabetes · doi:10.2337/db16-0305 · Cited by 46
Effect of Myoinositol and Antioxidants on Sperm Quality in Men with Metabolic Syndrome
Oliva, M. M., Minutolo, E., Lippa, A., Iaconianni, P., & Vaiarelli, A. (2016) · International Journal of Endocrinology · doi:10.1155/2016/1674950 · Cited by 48
Effects of Body Weight Reduction on Serum Irisin and Metabolic Parameters in Obese Subjects
Fukushima, Y., Kurose, S., Shinno, H., Thu, H. C. T., Takao, N., Tsutsumi, H., Hasegawa, T., Nakajima, T., & Kimura, Y. (2016) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2016.40.5.386 · Cited by 46
Insulin Resistance Is a Risk Factor for Silent Lacunar Infarction
Lee, J. E., Shin, D. W., Yun, J. M., Kim, S. H., Nam, Y., Cho, B., Lim, J., Jeong, H., Kwon, H., & Park, J. (2016) · Stroke · doi:10.1161/strokeaha.116.014097 · Cited by 47
Moreno‐Castellanos, N., Rodrı́guez, A., Rabanal‐Ruiz, Y., Fernández-Vega, A., López‐Miranda, J., Vázquez‐Martínez, R., Frühbeck, G., & Malagón, M. M. (2016) · Diabetologia · doi:10.1007/s00125-016-4155-5 · Cited by 47
von Düring, M. E., Jenssen, T. G., Bollerslev, J., Åsberg, A., Godang, K., & Hartmann, A. (2016) · Clinical Transplantation · doi:10.1111/ctr.12869 · Cited by 49
Ji, B., Qu, H., Wang, H., et al. (2016) · Angiology · doi:10.1177/0003319716682120 · Cited by 46
Ricklefs, K., Johnston, C. S., & Sweazea, K. L. (2017) · Obesity Medicine · doi:10.1016/j.obmed.2017.01.002 · Cited by 46
Aissaoui, O., Amiali, M., Bouzid, N., Belkacemi, K., & Bitam, A. (2017) · Pharmaceutical Biology · doi:10.1080/13880209.2017.1300820 · Cited by 49
Kobayashi, Y., Hara, N., Sugimoto, R., Mifuji‐Moroka, R., Tanaka, H., Eguchi, A., Iwasa, M., Hasegawa, H., Iwata, K., Takei, Y., et al. (2017) · Internal Medicine · doi:10.2169/internalmedicine.56.7796 · Cited by 47
Prevalence of Pancreatic Cystic Lesions Is Associated With Diabetes Mellitus and Obesity
Mizuno, S., Isayama, H., Nakai, Y., Yoshikawa, T., Ishigaki, K., Matsubara, S., Yamamoto, N., Ijichi, H., Tateishi, K., Tada, M., et al. (2017) · Pancreas · doi:10.1097/mpa.0000000000000833 · Cited by 47
Ferreira, M. A., Gomes, A. P. O., de Moraes, A. P. G., Stringhini, M. L. F., Mota, J. F., Coelho, A. S. G., & Botelho, P. B. (2017) · Clinical Nutrition ESPEN · doi:10.1016/j.clnesp.2017.08.008 · Cited by 48
Caimari, A., Bas-Prior, J. M. D., Boqué, N., Crescenti, A., Puiggròs, F., Chenoll, E., Martorell, P., Ramón, D., Genovés, S., & Arola, L. (2017) · Journal of Functional Foods · doi:10.1016/j.jff.2017.09.029 · Cited by 48
The resting perfusion pattern associates with functional decline in type 2 diabetes
Dai, W., Duan, W., Alfaro, F. J., Gavrieli, A., Kourtelidis, F., & Novak, V. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.09.004 · Cited by 47
Buscemi, S., Corleo, D., Vasto, S., Buscemi, C., Massenti, M. F., Nuzzo, D., Lucisano, G., Barile, A. M., Rosafio, G., Maniaci, V., et al. (2017) · International Journal of Obesity · doi:10.1038/ijo.2017.255 · Cited by 49
Giardina, S., Hernández‐Alonso, P., Díaz‐López, A., Salas‐Huetos, A., Salas‐Salvadó, J., & Bulló, M. (2017) · Clinical Nutrition · doi:10.1016/j.clnu.2017.11.014 · Cited by 47
Öztürk, K., Doğan, T., Çelikkanat, S., Özen, A., Demirci, H., Kurt, Ö., Türker, T., Yilmaz, Y. N., & Uygun, A. (2018) · European Journal of Gastroenterology & Hepatology · doi:10.1097/meg.0000000000001059 · Cited by 46
Modifications of Resting Energy Expenditure After Sleeve Gastrectomy
Bettini, S., Bordigato, E., Fabris, R., Serra, R., Prà, C. D., Belligoli, A., Sanna, M., Compagnin, C., D, M. F. M., Prevedello, L., et al. (2018) · Obesity Surgery · doi:10.1007/s11695-018-3190-3 · Cited by 46
Aryan, Z., Ghajar, A., Faghihi‐Kashani, S., Afarideh, M., Nakhjavani, M., & Esteghamati, A. (2018) · Annals of Nutrition and Metabolism · doi:10.1159/000488537 · Cited by 51
Roh, E., Kim, K. M., Park, K. S., Kim, Y. J., Chun, E. J., Choi, S. H., Park, K. S., Jang, H. C., & Lim, S. K. (2018) · Diabetes Obesity and Metabolism · doi:10.1111/dom.13447 · Cited by 47
Abdel-Sattar, E. A., Mehanna, E. T., El-Ghaiesh, S. H., et al. (2018) · Frontiers in Pharmacology · doi:10.3389/fphar.2018.00990 · Cited by 46
Li, X., Yin, J., Zhu, Y., Wang, X., Hu, X., Bao, W., Huang, Y., Chen, L., Chen, S., Yang, W. Q., et al. (2018) · Nutrients · doi:10.3390/nu10101403 · Cited by 48
Umano, G. R., Shabanova, V., Pierpont, B. M., Mata, M., Nouws, J., Tricò, D., Galderisi, A., Santoro, N., & Caprio, S. (2018) · International Journal of Obesity · doi:10.1038/s41366-018-0227-6 · Cited by 47
Impaired glucose metabolism in bipolar patients and response to mood stabilizer treatments
Steardo, L., Fabrazzo, M., Sampogna, G., Monteleone, A. M., D’Agostino, G., Monteleone, P., & Maj, M. (2018) · Journal of Affective Disorders · doi:10.1016/j.jad.2018.10.360 · Cited by 51
Sepúlveda-Villegas, M., Román, S., Rivera‐Íñiguez, I., Ojeda‐Granados, C., González-Aldaco, K., Torres-Reyes, L. A., José-Ábrego, A., & Panduro, A. (2019) · PLoS ONE · doi:10.1371/journal.pone.0208926 · Cited by 47
Baldani, D. P., Škrgatić, L., Kasum, M., Zlopaša, G., Oguić, S. K., & Herman, M. (2019) · Gynecological Endocrinology · doi:10.1080/09513590.2018.1534096 · Cited by 46
Khoshi, A., Bajestani, M. K., Shakeri, H., Goodarzi, G., & Azizi, F. (2019) · Lipids in Health and Disease · doi:10.1186/s12944-019-1085-5 · Cited by 49
Gruzdeva, O. V., Учасова, Е. Г., Dyleva, Y. A., Borodkinа, D. A., Евгеньевна, А. О., Antonova, L. V., Матвеева, В. Г., Belik, E. V., Ivanov, S. V., Sotnikov, A., et al. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.02163 · Cited by 48
Lin, R., Wu, D., Wu, F., Meng, Y., Zhang, J.-H., Wang, X.-G., & Jia, L. (2019) · Frontiers in Endocrinology · doi:10.3389/fendo.2019.00620 · Cited by 46
Benmassaoud, A., Ghali, P., Cox, J., Wong, P. Y. N., Szabo, J., Deschênes, M., Osikowicz, M., Lebouché, B., Klein, M. B., & Sebastiani, G. (2018) · PLoS ONE · doi:10.1371/journal.pone.0191985 · Cited by 46
Chissini, R. D. B. C., Kuschnir, M. C. C., de Oliveira, C. L., Giannini, D. T., & Santos, B. (2019) · Nutrition · doi:10.1016/j.nut.2019.110608 · Cited by 46
Effects of ERβ and ERα on OVX-induced changes in adiposity and insulin resistance
Zidon, T. M., Padilla, J., Fritsche, K. L., Welly, R. J., McCabe, L., Stricklin, O. E., Frank, A. P., Park, Y.-M., Clegg, D. J., Lubahn, D. B., et al. (2020) · Journal of Endocrinology · doi:10.1530/joe-19-0321 · Cited by 48
Choromańska, B., Myśliwiec, P., Łuba, M., Wojskowicz, P., Dadan, J., Myśliwiec, H., Choromańska, K., Zalewska, A., & Maciejczyk, M. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9040976 · Cited by 47
Circulating levels of Meteorin-like protein in polycystic ovary syndrome: A case-control study
Fouani, F. Z., Fadaei, R., Moradi, N., Zandieh, Z., Ansaripour, S., Yekaninejad, M. S., Vatannejad, A., & Mahmoudi, M. (2020) · PLoS ONE · doi:10.1371/journal.pone.0231943 · Cited by 50
Kimura, Y., Yoshida, D., Hirakawa, Y., Hata, J., Honda, T., Shibata, M., Sakata, S., Uchida, K., Kitazono, T., & Ninomiya, T. (2020) · Journal of Diabetes Investigation · doi:10.1111/jdi.13377 · Cited by 55
Martínez‐Sánchez, F. D., Vargas-Abonce, V. P., Guerrero-Castillo, A. P., Santos-Villavicencio, M. D. L., Eseiza-Acevedo, J., Meza-Arana, C. E., Gulías-Herrero, A., & Gómez-Sámano, M. Á. (2020) · Primary care diabetes · doi:10.1016/j.pcd.2020.10.006 · Cited by 48
Sjöros, T., Vähä‐Ypyä, H., Laine, S., Garthwaite, T., Lahesmaa, M., Laurila, S., Latva‐Rasku, A., Savolainen, A., Miikkulainen, A., Löyttyniemi, E., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-77637-3 · Cited by 50
Hadi, S., Daryabeygi‐Khotbehsara, R., Mirmiran, P., McVicar, J., Hadi, V., Soleimani, D., & Askari, G. (2021) · Phytotherapy Research · doi:10.1002/ptr.6990 · Cited by 46
Moradi, N., Fouani, F. Z., Vatannejad, A., Arani, A. B., Shahrzad, S., & Fadaei, R. (2021) · Lipids in Health and Disease · doi:10.1186/s12944-021-01514-9 · Cited by 46
Moderate dietary salt restriction increases vascular and systemic insulin resistance
Feldman, R. D. (1999) · American Journal of Hypertension · doi:10.1016/s0895-7061(99)00016-3 · Cited by 45
Kim, C. S., Park, J., Park, J. S., Kang, E. S., Ahn, C. W., Cha, B., Lim, S., Kim, K.-R., & Lee, H. (2006) · Obesity · doi:10.1038/oby.2006.133 · Cited by 46
Ko, G. T. C., & Tang, J. (2007) · Obesity · doi:10.1038/oby.2007.336 · Cited by 46
Wampers, M., Hanssens, L., van Winkel, R., Heald, A. H., Collette, J., Peuskens, J., Reginster, J., Scheen, A. J., & Binder, M. D. (2011) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2011.03.010 · Cited by 46
Insulin resistance in hypertension and cardiovascular disease
Lamounier‐Zepter, V., Ehrhart‐Bornstein, M., & Bornstein, S. R. (2006) · Best Practice & Research Clinical Endocrinology & Metabolism · doi:10.1016/j.beem.2006.07.002 · Cited by 46
Alvarez, M. M., Vieira, A. C. R. E., Moura, A. S., & da Veiga, G. V. (2006) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2006.03.018 · Cited by 46
Kalaitzakis, E., Sadik, R., Holst, J. J., Öhman, L., & Bjornsson, E. S. (2008) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2008.11.022 · Cited by 46
Otsuka, F., Sugiyama, S., Kojima, S., Maruyoshi, H., Funahashi, T., Sakamoto, T., Yoshimura, M., Kimura, K., Umemura, S., & Ogawa, H. (2007) · Circulation Journal · doi:10.1253/circj.71.1703 · Cited by 46
Aktürk, M., Altınova, A. E., Mert, İ., Buyukkagnici, U., Sargın, A., Arslan, M., & Danışman, N. (2008) · Journal of Endocrinological Investigation · doi:10.1007/bf03345611 · Cited by 47
Chistiakov, D. A., Potapov, V. A., Андреевна, С. С., Бельчикова, Л. Н., Суплотова, Л. А., & Nosikov, V. V. (2011) · Acta Diabetologica · doi:10.1007/s00592-011-0299-4 · Cited by 45
Jehle, S., Reyes, C. M., Sundeen, R. E., et al. (2005) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2004-1967 · Cited by 46
The Role of Ghrelin in Weight Gain and Growth in Epileptic Children Using Valproate
Güngör, S., Yücel, G., Akıncı, A., Tabel, Y., Özerol, İ. H., & Yoloğlu, S. (2007) · Journal of Child Neurology · doi:10.1177/0883073807307096 · Cited by 46
Tarantino, G., Conca, P., Coppola, A., Vecchione, R., & Minno, G. D. (2006) · European Journal of Clinical Investigation · doi:10.1111/j.1365-2362.2007.01745.x · Cited by 46
Association of Parity With Risk of Type 2 Diabetes and Related Metabolic Disorders
Hanley, A. J., McKeown‐Eyssen, G., Harris, S. B., Hegele, R. A., Wolever, T. M. S., Kwan, J., & Zinman, B. (2002) · Diabetes Care · doi:10.2337/diacare.25.4.690 · Cited by 46
Florez, H. J., Mendez, A. J., Casanova-Romero, P. Y., Larreal, C., Castillo-Florez, S., Lee, D. J., & Goldberg, R. B. (2005) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2005.10.013 · Cited by 46
Tuzcu, A., Yalakı, S., Arikan, S., Gökalp, D., Bahcec, M., & Tuzcu, Ş. A. (2009) · Pituitary · doi:10.1007/s11102-009-0183-1 · Cited by 45
Palacios, R., Santos, J., González, M., Ruiz, J., & Márquez, M. (2007) · International Journal of STD & AIDS · doi:10.1258/095646207780132415 · Cited by 46
Ratliff, J. C., Mutungi, G., Puglisi, M. J., Volek, J. S., & Fernández, M. L. (2009) · Nutrition Research · doi:10.1016/j.nutres.2009.03.007 · Cited by 48
Elevated Inflammation Markers in Pheochromocytoma Compared to Other Forms of Hypertension
Zelinka, T., Petrák, O., Štrauch, B., Holaj, R., Kvasnička, J., Mazoch, J., Pacák, K., & Widimsky, J., Jr. (2007) · NeuroImmunoModulation · doi:10.1159/000107289 · Cited by 46
Elevated Serum Leptin Concentrations in Women with Hyperuricemia.
Matsubara, M., Chiba, H., Maruoka, S., & Katayose, S. (2002) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.9.28 · Cited by 45
Wu, Y. J., Chen, L. S., & Qiang, W. G. (2006) · Liver International · doi:10.1111/j.1478-3231.2005.01219.x · Cited by 46
Koh, S. J., Hyun, Y. J., Choi, S. Y., Chae, J. S., Kim, J. Y., Park, S., Ahn, C., Jang, Y., & Lee, J. H. (2007) · Clinica Chimica Acta · doi:10.1016/j.cca.2007.11.017 · Cited by 46
Relation between Insulin Resistance and Breast Cancer among Chilean Women
Garmendia, M. L., Pereira, A. P. R., Alvarado, M. E., & Atalah, E. (2007) · Annals of Epidemiology · doi:10.1016/j.annepidem.2007.01.037 · Cited by 46
Gray, I. P., Cooper, P. A., Cory, B. J., Toman, M., & Crowther, N. J. (2002) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2001-011961 · Cited by 46
Andersen, N. H., Bojesen, A., Kristensen, K., Birkebæk, N., Fedder, J., Bennett, P., Christiansen, J. S., & Gravholt, C. H. (2008) · Clinical Endocrinology · doi:10.1111/j.1365-2265.2008.03211.x · Cited by 44
ADMA is independently related to flow‐mediated vasodilation in subjects at low cardiovascular risk
Ardigò, D., Stuehlinger, M., Franzini, L., Valtueña, S., Piatti, P., Pachinger, O. M., Reaven, G. M., & Zavaroni, I. (2007) · European Journal of Clinical Investigation · doi:10.1111/j.1365-2362.2007.01781.x · Cited by 46
Raatz, S. K., Rosenberger, T. A., Johnson, L. K., Wolters, W. W., Burr, G., & Picklo, M. J. (2013) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2012.09.022 · Cited by 46
Kalra, L., Rambaran, C., Chowienczyk, P., Goss, D. E., Hambleton, I. R., Ritter, J. M., Shah, A. M., Wilks, R., & Forrester, T. (2005) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/01.atv.0000183887.76087.6a · Cited by 46
Nakanishi, N., SHIRAISHI, T., & Wada, M. (2005) · Internal Medicine · doi:10.2169/internalmedicine.44.542 · Cited by 44
Effect of thiol antioxidant on body fat and insulin reactivity
Hildebrandt, W., Hamann, A., Krakowski‐Roosen, H., Kinscherf, R., Dugi, K. A., Sauer, R., Lacher, S., N�bel, N., Bodens, A., Bellou, V., et al. (2004) · Journal of Molecular Medicine · doi:10.1007/s00109-004-0532-5 · Cited by 46
QTc interval in a sample of long-term schizophrenia inpatients
Ramos‐Ríos, R., Arrojo, M., Silva, E. P., Carballal-Calvo, F., Bouzón-Barreiro, J. L., Seoane-Prado, J., Codesido-Barcala, R., Crespí-Armenteros, A., Fernández-Pérez, R., López-Moríñigo, J.-D., et al. (2009) · Schizophrenia Research · doi:10.1016/j.schres.2009.09.041 · Cited by 51
The hyperbolic equilibrium between insulin sensitivity and secretion
Pacini, G. (2006) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2005.10.014 · Cited by 46
Weiss, E. P., Arif, H., Villareal, D. T., Marzetti, E., & Holloszy, J. O. (2008) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/88.1.51 · Cited by 46
Tayama, K., Inukai, T., & Shimomura, Y. (1999) · Diabetes Research and Clinical Practice · doi:10.1016/s0168-8227(98)00118-1 · Cited by 46
Early Pregnancy Insulin Resistance and Subsequent Gestational Diabetes Mellitus
Smirnakis, K. V., Martinez, A., Blatman, K. S. H., Wolf, M. S., Ecker, J. L., & Thadhani, R. (2005) · Diabetes Care · doi:10.2337/diacare.28.5.1207 · Cited by 45
Suzuki, S., Wenyi, Z., Hirai, M., et al. (2004) · Peptides · doi:10.1016/j.peptides.2004.03.030 · Cited by 46
Thyssen, J. P., Linneberg, A. R., Carlsen, B. C., Johansen, J. D., Engkilde, K., Hansen, T. F., Pociot, F., Pedersen, O. B., Meldgaard, M., Szecsi, P. B., et al. (2011) · BMJ Open · doi:10.1136/bmjopen-2011-000062 · Cited by 46
Borges, P. K. D. O., Gimeno, S. G. A., Tomita, N. E., & Ferreira, S. R. G. (2007) · Cadernos de Saúde Pública · doi:10.1590/s0102-311x2007000300024 · Cited by 46
Vincent, S., Gerber, M., Mc, B., Defoort, C., Loundou, A., Portugal, H., Planells, R., Juhan-Vague, I., Charpiot, P., Grolier, P., et al. (2004) · Public Health Nutrition · doi:10.1079/phn2003547 · Cited by 45
Robinson, M., Scheuermann‐Freestone, M., Leeson, P., Channon, K. M., Clarke, K., Neubauer, S., & Wiesmann, F. (2008) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/1532-429x-10-10 · Cited by 46
Fogari, R., Preti, P. S., Zoppi, A., Lazzari, P., Corradi, L., Fogari, E., Ciccarelli, L., & Derosa, G. (2006) · European Journal of Clinical Pharmacology · doi:10.1007/s00228-006-0176-1 · Cited by 46
Cardiovascular risk factors in young Gypsy population
Krajcovicová-Kudlácková, M., Blazicek, P., Spustová, V., et al. (2004) · Bratislavské lekárske listy/Bratislava medical journal · doi:10.1007/bf03656680 · Cited by 46
Boguszewski, C. L., Meister, L. H. F., Zaninelli, D. C. T., & Radominski, R. B. (2005) · European Journal of Endocrinology · doi:10.1530/eje.1.01817 · Cited by 46
Kashiwabara, H., Inaba, M., Maruno, Y., Morita, T., Awata, T., Negishi, K., Iitaka, M., & Katayamá, S. (2000) · Journal of Hypertension · doi:10.1097/00004872-200018010-00012 · Cited by 54
Wu, K., Hsiao, C., Ho, L.-T., Sheu, W. H., Pei, D., Chuang, L., Curb, D. J., Chen, Y.-D. I., Tsai, H.-J., Dzau, V. J., et al. (2002) · Hypertension Research · doi:10.1291/hypres.25.529 · Cited by 46
Association of Nonalcoholic Fatty Liver Disease With Insulin Resistance
Sargın, M., li, O. U. B., Sargın, H., Orbay, E., & Yayla, A. (2003) · Journal of Clinical Gastroenterology · doi:10.1097/00004836-200311000-00010 · Cited by 46
Umeda, M., Kanda, T., & Murakami, M. (2003) · Hypertension Research · doi:10.1291/hypres.26.485 · Cited by 46
Guerci, B., Vergès, B. L., Durlach, V., Hadjadj, S., Drouin, P., & Paul, J. L. (2000) · International Journal of Obesity · doi:10.1038/sj.ijo.0801181 · Cited by 46
Bitnun, A., Sochett, E. B., Dick, P. T., To, T. M., Jefferies, C., Babyn, P., Forbes, J. C., Read, S., & King, S. (2005) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2004-0125 · Cited by 46
Baratta, R., Paola, R. D., Spampinato, D., Fini, G., Marucci, A., Coco, A., Vigneri, R., Frittitta, L., & Trischitta, V. (2003) · Journal of Molecular Medicine · doi:10.1007/s00109-003-0466-3 · Cited by 46
Hämäläinen, H., Rönnemaa, T., Virtanen, A., Lindström, J., Eriksson, J. G., Valle, T. T., Ilanne‐Parikka, P., Keinanen-Kiukaanniemi, S. M., Rastas, M., Aunola, S., et al. (2005) · Diabetologia · doi:10.1007/s00125-005-1938-5 · Cited by 45
Osei, K., Gaillard, T. R., Kaplow, J. M., Bullock, M., & Schuster, D. (2004) · Metabolism · doi:10.1016/j.metabol.2004.06.023 · Cited by 46
Lagerpusch, M., Bosy-Westphal, A., Kehden, B., Peters, A., & Müller, M. J. (2012) · International Journal of Obesity · doi:10.1038/ijo.2011.211 · Cited by 45
Glucose Intolerance after a Recent History of Gestational Diabetes Based on the 2013 WHO Criteria
Benhalima, K., Jegers, K., Devlieger, R., Verhaeghe, J., & Mathieu, C. (2016) · PLOS ONE · doi:10.1371/journal.pone.0157272 · Cited by 45
Bernardi, J. R., Ferreira, C. F., Senter, G., Krolow, R., de Aguiar, B. W., Portella, A. K., Kauer-Sant'Anna, M., Kapczinski, F., Dalmaz, C., Goldani, M. Z., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0062031 · Cited by 43
Metadata
- Authors
- Matthews, D. R., Hosker, J. P., Rudenski, A. S., Naylor, B. A., Treacher, D. F., & Turner, R. C.
- Affiliations
- University of Oxford (GB)
- ORCID
- Matthews, D. R.
- Venue
- Diabetologia
- Published
- 1985-07
- Volume
- 28
- Issue
- 7
- Pages
- 412-419
- ISSN
- 0012-186X (ISSN-L)
- 1432-0428
- OpenAlex
- W2160234571
- Cited by
- 31,502
- References
- 21
- Citations by year
- 2026: 933 · 2025: 1060 · 2024: 1240 · 2023: 1291 · 2022: 1489 · 2021: 1528 · 2020: 1424 · 2019: 1427 · 2018: 1456 · 2017: 1440 · 2016: 1481 · 2015: 1682 · 2014: 1693 · 2013: 1621 · 2012: 1518
- FWCI
- 7.91
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Diabetologia (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Medical Research Council
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Pancreatic function and diabetes
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- HOMA, insulin resistance, beta-cell function, fasting blood glucose, fasting insulin, hyperglycaemic clamp, euglycaemic clamp, intravenous glucose tolerance test, insulin receptor binding, type 2 diabetes
- MeSH terms
- Adult, Blood Glucose, Computers, Diabetes Mellitus, Type 2, Erythrocytes, Fasting, Homeostasis, Humans, Insulin, Insulin Resistance, Islets of Langerhans, Middle Aged, Monocytes, Receptor, Insulin
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-14, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-14 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review