Proceedings of the 2018 Advances In Motility and In NeuroGastroenterology
Bibliographic record
Abstract
OBJECTIVES: Motility and functional disorders are common in children and often debilitating, yet these disorders remain challenging to treat effectively. At the 2018 Annual North American Society for Pediatric Gastroenterology, Hepatology and Nutrition meeting, the Neurogastroenterology and Motility Committee held a full day symposium entitled, 2018 Advances In Motility and In NeuroGastroenterology - AIMING for the future. The symposium aimed to explore clinical paradigms in pediatric gastrointestinal motility disorders and provided a foundation for advancing new scientific and therapeutic research strategies. METHODS: The symposium brought together leading experts throughout North America to review the state of the art in the diagnosis and management of motility and functional disorders in children. Presentations were divided into esophageal, antral duodenal, and colorectal modules. Each module included oral presentations by experts in the respective fields, leading to thought-provoking discussions. There were 2 breakout sessions with small group discussions on select topics, focusing on defining scientific insights into the diagnosis and management of pediatric functional gastrointestinal and motility disorders in a systematic, segment-based approach. CONCLUSIONS: The field of neurogastroenterology has made remarkable progress in the last decade. The current report summarizes the major learning points from the symposium highlighting the diagnosis and promising therapies on the horizon for pediatric neurogastrointestinal and motility disorders.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.062 | 0.023 |
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".