Type 2 Polarized Memory B cells Hold Allergen-Specific IgE Memory
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.
Bibliographic record
Abstract
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.130 | 0.055 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it