Curriculum for neurogastroenterology and motility training: A report from the joint <scp>ANMS</scp>‐<scp>ESNM</scp> task force
Bibliographic record
Abstract
Although neurogastroenterology and motility (NGM) disorders are some of the most frequent disorders encountered by practicing gastroenterologists, a structured competency-based training curriculum developed by NGM experts is lacking. The American Neurogastroenterology and Motility Society (ANMS) and the European Society of Neurogastroenterology and Motility (ESNM) jointly evaluated the components of NGM training in North America and Europe. Eleven training domains were identified within NGM, consisting of functional gastrointestinal disorders, visceral hypersensitivity and pain pathways, motor disorders within anatomic areas (esophagus, stomach, small bowel and colon, anorectum), mucosal disorders (gastro-esophageal reflux disease, other mucosal disorders), consequences of systemic disease, consequences of therapy (surgery, endoscopic intervention, medications, other therapy), and transition of pediatric patients into adult practice. A 3-tiered training curriculum covering these domains is proposed here and endorsed by all NGM societies. Tier 1 NGM knowledge and training is expected of all gastroenterology trainees and practicing gastroenterologists. Tier 2 knowledge and training is appropriate for trainees who anticipate NGM disorder management and NGM function test interpretation being an important part of their careers, which may require competency assessment and credentialing of test interpretation skills. Tier 3 knowledge and training is undertaken by trainees interested in a dedicated NGM career and may be restricted to specific domains within the broad NGM field. The joint ANMS and ESNM task force anticipates that the NGM curriculum will streamline NGM training in North America and Europe and will lead to better identification of centers of excellence where Tier 2 and Tier 3 training can be accomplished.
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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 | 0.021 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".