Ontogeny and genetic correlates of the TLR mediated pediatric innate immune response
Bibliographic record
Abstract
In early life, humans are particularly vulnerable to morbidity and mortality due to infectious disease. A key system that is critical to both early response to pathogens, and also to the success or failure of a vaccine to induce protective immunity is the innate immune system. It is our working hypothesis that changes in the developing immune system mediate changes in both vaccine response and infectious morbidity and mortality. This thesis presents published and unpublished work wherein we analyze the innate immune response of a defined population of newborns from the greater Vancouver area in British Columbia, Canada. In this work, we set out to define the development of early response by the human infant immune system to molecular danger signals known as pathogen-associated molecular patterns (PAMPS) by the well-defined Toll-Like Receptor (TLR) system expressed by peripheral blood mononuclear cells (PBMC). In addition, we have correlated this response with the occurrence of pertinent genetic variance between individuals, in the hope of identifying immune modulating variants in situ. Such variants will provide the basis for later testing of our hypothesis that genetic variance in early life innate immune response contributes to the significant variability in morbidity and mortality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".