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Record W2978051885 · doi:10.3233/hab-190396

The modified vaccination technique designed to prevent and cure acute and chronic disorders

2019· review· en· W2978051885 on OpenAlexaff
A. Z. Barabas, Chad Cole, Zoltán Kovács, Erno I. Kovacs, René Lafrenière, D. M. Weir

Bibliographic record

VenueHuman Antibodies · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsImmune systemVaccinationImmunologyMedicineDiseaseAutoimmune diseaseAntibodyAutoimmunityImmune toleranceInternal medicine

Abstract

fetched live from OpenAlex

In spite of enormous efforts there have been no solutions to date for preventing/terminating certain acute and chronic disorders of humans by vaccination or drugs. Yet it is well understood that if the target antigen (ag) could be presented appropriately to the cells of the immune system then solutions could be found. Recently, the Barabas research group has introduced and described the third vaccination method - called modified vaccination technique (MVT) - which has the ability to provide a corrective immune response in experimental animals with an autoimmune kidney disease. Injections of immune complexes - made up of the target ag and specific non-pathogenic IgM antibodies directed against the target ag - achieved downregulation of pathogenic immune responses and tolerance to self was regained. Utilizing the immune system's natural abilities to respond to corrective information, the MVT technique was able to prevent an autoimmune kidney disease from occurring (prophylactic effect) in experimental animals, and when present, terminating it (therapeutic effect) specifically and without measurable side effects.It is predicted that the application of the MVT will have the potential in the future to revolutionize the preventative and therapeutic options for dealing with chronic disorders in humans (such as autoimmune disease, cancer and acute chronic infections) and achieve cures.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.822

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 head0.015
GPT teacher head0.313
Teacher spread0.297 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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