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Negative Regulation of Immunoreceptor Signaling

2002· review· en· W2147026827 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

VenueAnnual Review of Immunology · 2002
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsMcGill UniversityUniversité de MontréalMontreal Clinical Research Institute
FundersNational Cancer InstituteInstitut National de la Santé et de la Recherche MédicaleCentre National de la Recherche ScientifiqueAssociation pour la Recherche sur le Cancer
KeywordsBiologyImmunoreceptor tyrosine-based activation motifProtein tyrosine phosphataseSignal transductionCell biologySignal transducing adaptor proteinPhosphorylationReceptorReceptor tyrosine kinaseKinaseTyrosine phosphorylationTyrosineBiochemistrySH2 domain

Abstract

fetched live from OpenAlex

Immune cells are activated as a result of productive interactions between ligands and various receptors known as immunoreceptors. These receptors function by recruiting cytoplasmic protein tyrosine kinases, which trigger a unique phosphorylation signal leading to cell activation. In the recent past, there has been increasing interest in elucidating the processes involved in the negative regulation of immunoreceptor-mediated signal transduction. Evidence is accumulating that immunoreceptor signaling is inhibited by complex and highly regulated mechanisms that involve receptors, protein tyrosine kinases, protein tyrosine phosphatases, lipid phosphatases, ubiquitin ligases, and inhibitory adaptor molecules. Genetic evidence indicates that this inhibitory machinery is crucial for normal immune cell homeostasis.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.023
GPT teacher head0.296
Teacher spread0.273 · 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