Bench-to-bedside review: Association of genetic variation with sepsis
Bibliographic record
Abstract
Susceptibility and response to infectious disease is, in part, heritable. Initial attempts to identify the causal genetic polymorphisms have not been entirely successful because of the complexity of the genetic, epigenetic, and environmental factors that influence susceptibility and response to infectious disease and because of flaws in study design. Potential associations between clinical outcome from sepsis and many inflammatory cytokine gene polymorphisms, innate immunity pathway gene polymorphisms, and coagulation cascade polymorphisms have been observed. Confirmation in large, well conducted, multicenter studies is required to confirm current findings and to make them clinically applicable. Unbiased investigation of all genes in the human genome is an emerging approach. New, economical, high-throughput technologies may make this possible. It is now feasible to genotype thousands of tag single nucleotide polymorphisms across the genome in thousands of patients, thus addressing the issues of small sample size and bias in selecting candidate polymorphisms and genes for genetic association studies. By performing genome-wide association studies, genome-wide scans of nonsynonymous single nucleotide polymorphisms, and testing for differential allelic expression and copy number polymorphisms, we may yet be able to tease out the complex influence of genetic variation on susceptibility and response to infectious 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".