Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over the past years, eosinophils have become a focus of scientific interest, especially in the context of their recently uncovered functions (e.g. antiviral, anti-inflammatory, regulatory). These versatile cells display both beneficial and detrimental activities under various physiological and pathological conditions. Eosinophils are involved in the pathogenesis of many diseases which can be classified into primary (clonal) and secondary (reactive) disorders and idiopathic (hyper)eosinophilic syndromes. Depending on the biological specimen, the eosinophil count in different body compartments may serve as a biomarker reflecting the underlying pathophysiology and/or activity of distinct diseases and as a therapy-driving (predictive) and monitoring tool. Personalized selection of an appropriate therapeutic strategy directly or indirectly targeting the increased number and/or activity of eosinophils should be based on the understanding of eosinophil homeostasis including their interactions with other immune and non-immune cells within different body compartments. Hence, restoring as well as maintaining homeostasis within an individual's eosinophil pool is a goal of both specific and non-specific eosinophil-targeting therapies. Despite the overall favourable safety profile of the currently available anti-eosinophil biologics, the effect of eosinophil depletion should be monitored from the perspective of possible unwanted consequences.
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.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 it