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Record W2560802610 · doi:10.1177/1087057116681407

Identification of Inhibitors of the Association of ZAP-70 with the T Cell Receptor by High-Throughput Screen

2016· article· en· W2560802610 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

VenueSLAS DISCOVERY · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsDiscovery Centre
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthNational Institute of Arthritis and Musculoskeletal and Skin DiseasesHoward Hughes Medical Institute
KeywordsReceptorSignal transductionCell biologyT-cell receptorT cellIntracellularCellAntigenBiologyChemistryMolecular biologyImmunologyBiochemistryImmune system

Abstract

fetched live from OpenAlex

ZAP-70 is a critical molecule in the transduction of T cell antigen receptor signaling and the activation of T cells. Upon activation of the T cell antigen receptor, ZAP-70 is recruited to the intracellular ζ-chains of the T cell receptor, where ZAP-70 is activated and colocalized with its substrates. Inhibitors of ZAP-70 could potentially function as treatments for autoimmune diseases or organ transplantation. In this work, we present the design, optimization, and implementation of a screen for inhibitors that would disrupt the interaction between ZAP-70 and the T cell antigen receptor. The screen is based on a fluorescence polarization assay for peptide binding to ZAP-70.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.218

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 head0.004
GPT teacher head0.182
Teacher spread0.179 · 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