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Record W4406186554 · doi:10.1016/j.ajt.2024.12.158

Simultaneous Islet Kidney Transplantation in Patients Declined for Pancreas Transplant: Initial Experience at a North American Transplant Center

2025· article· en· W4406186554 on OpenAlexaff
Catherine Parmentier, Abdulmohsen Bakhsh, Paraish S. Misra, Justin Manuel, Hongtao Gu, Xue‐Zhong Ma, Shagani Thisairajah, Jennifer Coleman, Zaneta Sawicka, Andrea Norgate, Elmar Jaeckel, Jeffrey Schiff, Chaya Shwaartz, Ian D. McGilvray, Markus Selzner, Trevor Reichman

Bibliographic record

VenueAmerican Journal of Transplantation · 2025
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineIsletPancreas transplantationPancreasTransplantationKidney transplantKidney transplantationKidneyInternal medicineGeneral surgerySurgeryInsulin

Abstract

fetched live from OpenAlex

Simultaneous Pancreas Kidney (SPK) transplantation is a highly effective treatment for patients with diabetes and end-stage renal disease. However, the risk of surgical complications makes SPK unsuitable for some patients. Simultaneous Islet Kidney (SIK) transplantation offers an alternative for these individuals. Despite the higher achievement of insulin independence observed with SPK, previous studies indicate that successful islet transplantation improves overall survival, cardiovascular outcomes, and kidney graft survival compared to kidney transplant alone.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.299
Teacher spread0.290 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractno

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