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Record W2042174671 · doi:10.3727/000000006783982133

Estimation of Pancreas Weight from Donor Variables

2006· article· en· W2042174671 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCell Transplantation · 2006
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of AlbertaCapital District Health Authority
Fundersnot available
KeywordsEstimationPancreasComputer scienceStatisticsMedicineInternal medicineMathematicsEngineering

Abstract

fetched live from OpenAlex

Previous studies have identified several donor factors affecting the outcome of islet isolation. Pancreas weight has not been considered as a donor selection criterion, because a value cannot be obtained prior to organ procurement. However, a larger pancreas will likely contain a higher number of islets. Therefore, the prediction of pancreas weight would be helpful in donor selection, benefiting cost and efficiency of the islet isolation laboratory. The purpose of this study was to investigate normal pancreas weight in cadaveric donors and identify pancreas weight predictors from demographic data of cadaveric organ donors. We retrospectively analyzed data on pancreas weight from 354 cadaveric donors with respect to gender, age, body weight, body height, body mass index (BMI), and body surface area (BSA). In men, pancreas weight correlated more closely with body weight than with age, height, or BMI. BSA was as strong a correlate of pancreas weight as body weight. In women, pancreas weight had a similar pattern of relationships, with generally lower correlation coefficients. On the basis of the observation of gender-specific pancreas weight difference in elderly donors, stepwise multiple linear regression analyses were conducted separately for younger (< or =40 years) and elderly (> or =41 years) donors. In younger donors, body weight and age were the major predictors of pancreas weight [pancreas weight (g) = 4.355 + 0.742 x body weight (kg) + 0.837 x age (years) (R2 = 0.564, p < 0.001)]. In contrast, pancreas weight of elderly donors was best predicted by BSA and gender [pancreas weight (g) = -17.624 + 60.036 x BSA (m2) - 7.152 x gender (R2 = 0.372, p < 0.001; "gender": 1 = female, 0 = male)]. Pancreas weight was found to be positively associated with pre- and postpurification islet yields. These formulae should contribute to the estimation of pancreas weight, and thus improve donor selection for islet isolation and transplantation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.207
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it