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Record W4244693063 · doi:10.3410/f.718339908.793555480

Faculty Opinions recommendation of New insights into the DT40 B cell receptor cluster using a proteomic proximity labeling assay.

2019· dataset· en· W4244693063 on OpenAlexaff
Laura Trinkle‐Mulcahy

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2019
Typedataset
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsUniversity of Ottawa
FundersNational Key Research and Development Program of ChinaBiotechnology and Biological Sciences Research CouncilMinistry of Science and Technology of the People's Republic of ChinaMedical Research CouncilDirectorate for Biological SciencesChinese Academy of SciencesSemmelweis EgyetemNational Natural Science Foundation of ChinaWellcome TrustDePaul University
KeywordsCluster (spacecraft)Computational biologyComputer scienceBiology

Abstract

fetched live from OpenAlex

Background: B cell receptor (BCR) clusters modulate BCR signaling in B-lymphocytes. Results: We used a quantitative proteomic proximity assay to analyze the BCR cluster in DT40 cells. Conclusion: Our proximity labeling assay identified novel components of the BCR cluster linked to integrin signaling. Significance: We provide new insights into BCR assembly and identify new and unexpected targets for further functional analysis.

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)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.156
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0020.002
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 head0.050
GPT teacher head0.364
Teacher spread0.313 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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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