Bibliographic record
Abstract
Neutrophils are considered to be central to the pathogenesis of most forms of acute lung injury (ALI). For the sake of clarity, neutrophil involvement in ALI can be conceptualized as consisting of sequential stages, beginning with their sequestration in the pulmonary microvasculature, followed by adhesion and activation, and culminating in the production of a microbicidal or "effector" response, such as the generation of reactive oxygen species or release of proteolytic enzymes. Great strides have been made in elucidating these various stages of neutrophil involvement. Recent studies have focused on the intracellular signaling pathways that govern neutrophil activation and have elucidated complex cascades of kinases and other intracellular signaling molecules that allow for amplication of the neutrophil response, yet simultaneously confer specificity of a response. We believe that the inflammatory response in ALI may initially be adaptive, such as the pivotal role played by neutrophils in a bacterial or fungal infection. Ultimately, it is the persistence or the dysregulation of neutrophil activation that may lead to ALI. An increased understanding of how neutrophils function will facilitate the design of therapeutic strategies that retain the beneficial aspects of the inflammatory response, while avoiding unnecessary tissue damage.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".