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Record W2289958404 · doi:10.15200/winn.144439.91844

Science AMA Series: We are a team of scientists, including diabetes specialist and dermatologists, trialling a new treatment for type 1 diabetes.

2015· dataset· en· W2289958404 on OpenAlexaboutno aff
bcdiabetes, r Science

Bibliographic record

VenueThe Winnower · 2015
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsnot available
Fundersnot available
KeywordsDiabetologyMedicineType 2 diabetesDiabetes mellitusRepurposingFamily medicineEndocrinology

Abstract

fetched live from OpenAlex

This is a pilot study to begin examining whether ustekinumab, a drug typically used for psoriasis, has the potential to reduce or eliminate the need for insulin injections in people with recently diagnosed Type 1 diabetes. “As one of the first clinical trials to target the immune cells that cause Type 1 diabetes, we are hopeful that this treatment will be a step towards finding a way to stop or slow the destruction of the body’s own insulin-producing cells.” Dr. Jan Dutz, Principal Investigator We are here to answer questions about diabetes, what this drug could mean for people with Type 1 diabetes, why we are looking at repurposing what seems like an unrelated medication, and anything else you’d like to ask us. http://www.bcdiabetes.ca/type1study/ Dr. Tom Elliott: Since 1992, Dr. Elliott has been a faculty member at UBC, where his current rank is Clinical Associate Professor. He was Co-Director of Undergraduate Medical Education for the UBC Division of Endocrinology from 1992 to 2012, and chaired the Endocrinology & Metabolism Society of BC, the professional body representing all BC endocrinologists and diabetes specialists, from 2008 to 2012. Also since 1992, Dr. Elliott has been on the active medical staff at Vancouver General Hospital, as well as conducting a busy private office practice in Endocrinology & Diabetology. Dr. Elliott is Director of Clinical Trials at BC Diabetes. He has authored more than 50 scientific papers and is actively engaged in 15 ongoing research projects. Dr. Ashish Marwaha Dr. Ashish Marwaha is a clinical pediatric academic who was appointed as a Radcliffe Travelling Fellow of University College, Oxford to pursue a PhD, in which he identified a novel subset of highly inflammatory immune cells (Th17) were present in children with new-onset type 1 diabetes (T1D) (Cutting Edge: Journal of Immunology, 2010). He has taken an active role in obtaining funding, designing, setting-up and running the current clinical trial of ustekinumab that will block the Th17 pathway in T1D.

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)0.005
metaresearch head score (Gemma)0.014
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: Dataset · Consensus signal: none
Teacher disagreement score0.165
Threshold uncertainty score0.551

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0060.004
Open science0.0020.002
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.1650.078

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 head0.047
GPT teacher head0.313
Teacher spread0.266 · 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
GenreDataset

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
Published2015
Admission routes1
Has abstractyes

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