Bibliographic record
Abstract
Dear Sir, We would like to thank Dr. Filik for giving us the opportunity to clarify several points in our manuscript, in which we systematically evaluated the utility of CRP and ESR in pediatric ulcerative colitis (UC) using four large datasets. This has been the largest and most comprehensive pediatric study to date but still, it is a post-hoc analysis from existing datasets. Therefore, several biases and limitations are inherent to the study design, including the inability to look at experimental genetic alterations associated with CRP response and the availability of longitudinal data on only a subset of the patient. Nonetheless, we aimed to observe the association between CRP and ESR, and disease activity, and not to elucidate the reasons for the differing CRP and ESR response. It is true that clinical response may precede resolution of elevated biomarkers when effective treatments are given, resulting in persistently elevated CRP and ESR in the presence of clinically quiescent disease. However, we found the opposite, namely that despite active disease many of the patients have normal or near-normal CRP and ESR; these biomarkers were more accurate in the severe end of the spectrum. We certainly agree that clinical remission with increased CRP may represent lack of mucosal healing and thus increased risk for relapse. However, this notion is much more relevant to Crohn's disease than for UC, where clinical symptoms are associated more closely with endoscopic appearance. Indeed, looking at our data (Figure 1)we can see that of the 84 children in clinical remission and 79 with mild disease, very few outliers had excessive elevation of CRP or ESR. We agree that UC patients in remission with increased CRP values should be further evaluated, but this is apparently an uncommon situation in UC, at least in children. We thus believe that our conclusions still hold: 1) CRP and ESR are sensitive in the more severe patients but not in reflecting mild disease activity; 2) if either test performs well in a given individual, there is no need to test also the other; and 3) on average, CRP performs slightly better than ESR in reflecting disease activity in pediatric UC.
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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 | 0.005 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.028 | 0.042 |
| Insufficient payload (model declined to judge) | 0.004 | 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".