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Record W6929986278 · doi:10.5281/zenodo.10244383

Type 2 Polarized Memory B cells Hold Allergen-Specific IgE Memory

2023· other· en· W6929986278 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typeother
Languageen
FieldMathematics
TopicStatistical Methods in Epidemiology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPython (programming language)PreprocessorScripting languageNormalization (sociology)B cellSource codeGenome

Abstract

fetched live from OpenAlex

R, python and shell code for Science Translational Medicine Manuscript adi0944 Human_10X_PreProcessing_Knudsen.R: Preprocessing of 10x genomics dataset for Seurat analysis, including QC filtering, cleaning, normalization and integration Koenig_Knudsen_Phelps_Bruton_et_al_Revised.R Code for creating the figures of the 10x genomics dataset of memory B cells FigureClusterFinal.csv: Cluster meta data used in Koenig_Knudsen_Phelps_Bruton_et_al_Revised.R tissue_allergy_analysis.R: Reanalysis of the Glass et al mass cytometry dataset IgE-cocluster analysis_long.txt: describes the Bulk IgE to 10x single cell sequencing co-clustering analysis and how the Shell and Python scripts are used in this process

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.217
Threshold uncertainty score0.727

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0040.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.2170.264

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 head0.174
GPT teacher head0.359
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2023
Admission routes1
Has abstractyes

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