Analysis of peripheral blood mononuclear cell data for finding a cellular signature of graft-versus-host disease
Bibliographic record
Abstract
GvHD is the most important complication of BMT. It has high morbidity and mortality. In an attempt to provide early prediction of GvHD, we analyzed PBMC data, together with GvHD outcome information, from a group of patients who underwent BMT. Various statistical methods were applied to overcome the difficulty arising from the high-dimensional longitudinal observations but with relatively small sample size. Analysis of “windowlized” data at a fixed time point did not find one subtype of PBMC or a subset of PBMCs that was important in the prediction of aGvHD. longitudinal data analysis indicated that proportions of T_ cells over time might separate well the patients with aGvHD and without aGvHD. This is consistent with the main finding in Lee (2006). In addition, we considered a two-level hierarchical model to describe the proportions of PBMCs. It indicates that T_cells CD3-CD8bdimCD8- is marginally associated with and disease.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".