Forward Genetic Dissection of Immunity to Infection in the Mouse
Bibliographic record
Abstract
Forward genetics is an experimental approach in which gene mapping and positional cloning are used to elucidate the molecular mechanisms underlying phenotypic differences between two individuals for a given trait. This strategy has been highly successful for the study of inbred mouse strains that show differences in innate susceptibility to bacterial, parasitic, fungal, and viral infections. Over the past 20 years, these studies have led to the identification of a number of cell populations and critical biochemical pathways and proteins that are essential for the early detection of and response to invading pathogens. Strikingly, the macrophage is the point of convergence for many of these genetic studies. This has led to the identification of diverse pathways involved in extracellular and intracellular pathogen recognition, modification of the properties and content of phagosomes, transcriptional response, and signal transduction for activation of adaptive immune mechanisms. In models of viral infections, elegant genetic studies highlighted the pivotal role of natural killer cells in the detection and destruction of infected cells.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".