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Record W1971136482 · doi:10.4161/onci.21205

Targeting the MHC Class II antigen presentation pathway in cancer immunotherapy

2012· article· en· W1971136482 on OpenAlex
Jacques Thibodeau, Marie‐Claude Bourgeois‐Daigneault, Réjean Lapointe

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOncoImmunology · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsCentre Hospitalier de l’Université de MontréalInstitute for Research in Immunology and CancerHôpital Notre-DameUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsImmunotherapyImmune systemCancer immunotherapyMHC class IImmunologyAntigen presentationMajor histocompatibility complexCancerMedicineAntigen processingAntigenCancer researchT cellInternal medicine

Abstract

fetched live from OpenAlex

The success of immunotherapy relies on the participation of all arms of the immune system and the role of CD4+ T lymphocytes in preventing tumor growth is now well established. Understanding how tumors evade immune responses holds the key to the development of cancer immunotherapies. In this review, we discuss how MHC Class II expression varies in cancer cells and how this influences antitumor immune responses. We also discuss the means that are currently available for harnessing the MHC Class II antigen presentation pathway for the development of efficient vaccines to activate the immune system against cancer.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.286
Teacher spread0.267 · 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