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Record W4307064167 · doi:10.56367/oag-036-10090

Preventing autoimmune diabetes in genetically susceptible people

2022· article· en· W4307064167 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOpen Access Government · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsImmunologyCLARITYAutoimmune diabetesAntigenSelf ToleranceDiabetes mellitusMechanism (biology)Autoimmune diseaseAutoimmunityBiologyMedicineImmune systemAntibodyEndocrinologyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Preventing autoimmune diabetes in genetically susceptible people Here, Professor Emeritus Peter Bretscher explores if we can now envisage antigen-specific therapies to prevent and treat organ-specific autoimmune diseases, such as autoimmune diabetes? He sketches for clarity the framework employed, as justified elsewhere. Most anti-self lymphocytes are eliminated as generated in primary lymphoid organs by the mechanism of central tolerance. A minority of self-antigens, such as insulin, are insufficiently present to cause complete central tolerance. Mature lymphocytes specific for peripheral self-antigens, and others specific for foreign antigens, are found in the periphery.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score1.000

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 science0.0010.004
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.282
Teacher spread0.272 · 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