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Record W2030081389 · doi:10.2741/3498

Preventing and treating chronic disorders using the modified vaccination technique

2009· review· en· W2030081389 on OpenAlex
A. Z. Barabas

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

VenueFrontiers in bioscience · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsUniversity of CalgaryHealth Sciences Centre
Fundersnot available
KeywordsVaccinationImmune systemMedicineImmunologyEx vivoAutoimmune diseaseDiseaseAntibodyAntigenIn vivoBiologyInternal medicine

Abstract

fetched live from OpenAlex

It is anticipated that the ultimate solution for the prevention and termination of autoimmune disorders will be based on somehow manipulating the cells of the immune system to attain antigen (ag) specific downregulation and termination. In the last few years we have developed a new vaccination technique that we call "modified vaccination technique" (MVT). It has with equal effectiveness both prevented and terminated autoimmune disease causing events in an experimental autoimmune kidney disease model. We expect that our technique will be similarly applicable to the specific treatment and cure of numerous other chronic disorders presently treated only by drugs. The vaccine is composed of two components, an ag and a specific antibody against it. When these are combined at slight ag excess they constitute a vaccine which is capable of treating chronic ailments by redirecting immune response outcomes in the vaccinated host. Both components, like drugs, will have to be produced ex vivo in order to maintain uniformity, safety, efficacy, and specificity.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score0.702

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 head0.013
GPT teacher head0.289
Teacher spread0.277 · 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