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Record W2317184785 · doi:10.3727/096368910x515872

Pancreatic Islet Culture and Preservation Strategies: Advances, Challenges, and Future Outlook

2010· review· en· W2317184785 on OpenAlexaff
Jamal Daoud, Lawrence Rosenberg, Maryam Tabrizian

Bibliographic record

VenueCell Transplantation · 2010
Typereview
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsMcGill University
Fundersnot available
KeywordsIsletTransplantationIn vitroPancreatic isletsScaffoldCell biologyComputer scienceBiologyMedicineBiotechnologyInternal medicineBiomedical engineeringInsulinBiochemistry

Abstract

fetched live from OpenAlex

Postisolation islet survival is a critical step for achieving successful and efficient islet transplantation. This involves the optimization of islet culture in order to prolong survival and functionality in vitro. Many studies have focused on different strategies to culture pancreatic islets in vitro through manipulation of culture media, surface modified substrates, and the use of various techniques such as encapsulation, embedding, scaffold, and bioreactor culture strategies. This review aims to present and discuss the different methodologies employed to optimize pancreatic islet culture in vitro as well as address their respective advantages and drawbacks.

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)0.000
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.028
GPT teacher head0.288
Teacher spread0.259 · 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

Citations62
Published2010
Admission routes1
Has abstractyes

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