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Current Status of Clinical Islet Transplantation

2005· review· en· W2012320162 on OpenAlexaboutno aff
Olle Korsgren, Bo Nilsson, Christian Berne, Marie Felldin, A. Foss, Ragnar Källén, Torbjörn Lundgren, K. Salmela, Annika Tibell, Gunnar Tufveson

Bibliographic record

VenueTransplantation · 2005
Typereview
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
Fundersnot available
KeywordsIsletTransplantationMedicineIslet cell transplantationDiabetes mellitusType 1 diabetesIntensive care medicineInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Islet transplantation is currently being explored as a treatment for patients with type 1 diabetes. At present, the number of patients becoming insulin-independent is rapidly increasing world-wide applying the transplantation protocol originally described by the group in Edmonton. A hallmark in this procedure is repeated infusions of islets obtained from 2 to 4 donors until normoglycemia is achieved. In order to establish islet transplantation as a widely accepted treatment modality, and make tolerance induction regimes applicable, it is essential that the donor:recipient ratio is brought down to 1:1. A conceivable strategy to achieve this goal in clinical islet transplantation is discussed.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.006

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 head0.141
GPT teacher head0.455
Teacher spread0.315 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations150
Published2005
Admission routes1
Has abstractyes

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