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Record W3164149256 · doi:10.1111/tri.13930

US food and drug administration (FDA) panel endorses islet cell treatment for type 1 diabetes: A pyrrhic victory?

2021· article· en· W3164149256 on OpenAlexaboutno aff
Lorenzo Piemonti, Axel Andrès, John Casey, Eelco J.P. de Koning, Marten A. Engelse, Robert Hilbrands, Paul Johnson, Bart Keymeulen, Julie Kerr‐Conte, Olle Korsgren, Roger Lehmann, Torbjörn Lundgren, Paola Maffi, François Pattou, F Saudek, James Shaw, Hanne Scholz, Steve White, Thierry Berney

Bibliographic record

VenueTransplant International · 2021
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
FundersNovo Nordisk FondenAgence Nationale de la Recherche
KeywordsMedicineIsletFood and drug administrationLicensureTransplantationDiabetes mellitusFamily medicineIntensive care medicineSurgeryPharmacologyMedical educationEndocrinology

Abstract

fetched live from OpenAlex

Allogeneic islet transplantation is a standard of care treatment for patients with labile type 1 diabetes in many countries around the world, including Japan, the United Kingdom, Australia, much of continental Europe, and parts of Canada. The United States is now endorsing islet cell treatment for type 1 diabetes, but the FDA has chosen to consider islets as a biologic that requires licensure, making the universal implementation of the procedure in the clinic very challenging and opening the manufacture of islet grafts to private companies. The commercialization of human tissues raises significant legal and ethical issues and ironically leads to a situation where treatments developed as a result of the scientific and economic efforts of academia over several decades become exploited exclusively by for-profit entities.

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)0.012
metaresearch head score (Gemma)0.019
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0100.011
Insufficient payload (model declined to judge)0.0320.009

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 head0.042
GPT teacher head0.275
Teacher spread0.233 · 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
GenreCommentary

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

Citations15
Published2021
Admission routes1
Has abstractyes

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Same venueTransplant InternationalSame topicPancreatic function and diabetesFrench-language works237,207