“Add-on” is scientifically more accurate than “Placebo control” in multiple Inflammatory Bowel Disease (IBD) trials
Bibliographic record
Abstract
Dear Editor, A genomic analysis of ≥75,000 cases and controls observed “considerable overlap between susceptibility loci for IBD and mycobacterial infection.” 1 An editorial in the New England Journal of Medicine stated “common genetic signatures support, albeit indirectly, the proposal that a proportion of Crohn's disease cases may have a mycobacte-rial cause.” 2 These observations lend considerable support to the increasing concern that IBD may be caused by a genetic susceptibility coupled with an associated mycobac-terial infection. We pose three critical questions. In light of the genetic findings and published evidence for anti-MAP activity of IBD therapies, we suggest that the term “placebo” has been used inappropriately in many prior IBD studies. The definition of the word “placebo” is open to multiple interpretations. Nevertheless, when used in reference to pharmaceutical medical trials it is generally accepted that the “placebo” group receives an inert substance that does not obviously influence the disease being evaluated.
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 | 0.034 | 0.211 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.033 | 0.025 |
| Insufficient payload (model declined to judge) | 0.016 | 0.013 |
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".