A Quantitative Assessment of Mucosal Eosinophils in the Gastrointestinal Tract of Children Without Detectable Organic Disease
Bibliographic record
Abstract
BACKGROUND: Accurate measurements of mucosal eosinophil concentrations in gastrointestinal tracts of healthy children are necessary to differentiate health and disease states in general, and better define eosinophilic gastrointestinal diseases. STUDY: We retrospectively reviewed gastrointestinal biopsies from children with macroscopically normal endoscopies, who, after a minimal follow-up of one year, were not diagnosed with any organic disease. Peak eosinophil concentrations and distributions were assessed from each segment of the gastrointestinal tract. RESULTS: ) were: esophagus 0 (0-0, 0-84), stomach 0 (0-4, 0-84), duodenal bulb 20 (13-30, 7-67), second part of duodenum 20 (13-29, 0-105), terminal ileum 29 (14-51, 0-247), cecum 53 (37-89, 10-232), ascending colon 55 (25-84, 0-236), transverse colon 38 (21-67, 4-181), descending colon 29 (17-59, 0-114), sigmoid colon 25 (13-40, 0-215) and rectum 13 (4-28, 0-152). Significant geographical variance was present, however, no differences in eosinophil concentrations were identified between children with resolving symptoms vs. those with functional diagnoses, nor across age groups. CONCLUSIONS: Standardized eosinophil concentrations from the gastrointestinal tracts of children without organic disease will serve to better define both health and disease states. No differences were found between resolved symptoms vs. functional diagnoses nor between age groups in this pediatric cohort.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".