Bibliographic record
Abstract
Dear Editor The authors thank Dr Impellizeri for his comments. Our strategy was purposeful. We proposed standards for the endoscopy, biopsy, and histopathological evaluation of inflammation in endoscopic biopsies of the gastrointestinal tract of dogs and cats, and, in our Guidelines, we outlined the advantages and disadvantages of biopsy derived by endoscopy (pages 13 and 14).1 An evidence-based medicine approach was used by the Group to develop the Consensus Statement. Where evidence was conflicting, ambiguous, or lacking, the Group adopted interpretive recommendations on the basis of its collective expertise.1 The evidence-based data in support of laparoscopy-derived biopsy of the jejunum, particularly with regard to safety, are still relatively minimal compared with that with endoscopy. Single-site intestinal biopsy (eg, jejunal biopsy as suggested by Dr Impellizeri2) may not readily diagnose the spectrum of gastrointestinal tract pathology in an individual patient. Two previous studies have shown poor correlation between duodenal and ileal histopathology with abnormalities sometimes more readily detected in ileal biopsy.a,3 Consequently, we recommended biopsy from at least 2 intestinal sites—with endoscopy, the biopsy sites would be duodenal and ileal.1 Whether jejunal biopsy further differentiates and clarifies gastrointestinal tract disease remains to be determined.
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".