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Record W2076931779 · doi:10.1155/2012/414812

Generation of Transplantable Beta Cells for Patient-Specific Cell Therapy

2012· article· en· W2076931779 on OpenAlexaff
Xiaojie Wang, Daniel L. Metzger, Mark Meloche, Jianqiang Hao, Ziliang Ao, Garth L. Warnock

Bibliographic record

VenueInternational Journal of Endocrinology · 2012
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineBeta cellBETA (programming language)ImmunosuppressionSomatic cellHeterologousCell therapyTransplantationCellIsletRegeneration (biology)Cancer researchInsulinImmunologyCell biologyInternal medicineBiologyBiochemistry

Abstract

fetched live from OpenAlex

Islet cell transplantation offers a potential cure for type 1 diabetes, but it is challenged by insufficient donor tissue and side effects of current immunosuppressive drugs. Therefore, alternative sources of insulin-producing cells and isletfriendly immunosuppression are required to increase the efficiency and safety of this procedure. Beta cells can be transdifferentiated from precursors or another heterologous (non-beta-cell) source. Recent advances in beta cell regeneration from somatic cells such as fibroblasts could circumvent the usage of immunosuppressive drugs. Therefore, generation of patient-specific beta cells provides the potential of an evolutionary treatment for patients with diabetes.

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 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 score0.093
Threshold uncertainty score0.337

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 head0.055
GPT teacher head0.296
Teacher spread0.240 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations4
Published2012
Admission routes1
Has abstractyes

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