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Record W2897943930 · doi:10.1097/mpg.0000000000002186

Updates in Pediatric Pancreatology

2018· article· en· W2897943930 on OpenAlexaff
Amit S. Grover, A. Jay Freeman, Maisam Abu‐El‐Haija, John F. Eisses, Timothy B. Gardner, Quin Y. Liu, Mark E. Lowe, Jaimie D. Nathan, Tonya M. Palermo, Vikesh K. Singh, Andrew T. Trout, Aliye Uç, Sohail Z. Husain, Véronique D. Morinville

Bibliographic record

VenueJournal of Pediatric Gastroenterology and Nutrition · 2018
Typearticle
Languageen
FieldMedicine
TopicPancreatitis Pathology and Treatment
Canadian institutionsMontreal Children's Hospital
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsMedicinePediatric gastroenterologyHepatologyInternal medicineGastroenterology

Abstract

fetched live from OpenAlex

The Pancreas Committee of the North American Society for Pediatric Gastroenterology, Hepatology and Nutrition aims to promote awareness of pediatric pancreatic diseases, support clinical and basic science research in the field, educate pediatric gastroenterologists, and advocate on behalf of pediatric patients with pancreatic disorders. At the 2017 Annual North American Society for Pediatric Gastroenterology, Hepatology and Nutrition meeting, the Pancreas Committee held a full day symposium on pediatric pancreatic diseases, entitled, "Frontiers in Pediatric Pancreatology." The symposium served as a timely and novel academic meeting that brought together individuals with a vested interest in the care of children with pancreatic disorders. The objective of this day-long course was to update practicing gastroenterologists on the latest advances in research, management algorithms, endoscopic therapies, radiographic resources, surgical approaches, and novel drug therapies targeted to pediatric pancreatitis. Presentations were divided into 4 modules: diagnosis, risk factors, and natural history of pancreatitis; pancreatic imaging and exocrine function; management of pancreatitis; and new frontiers in pediatric pancreatitis research. The course fostered a unique ecosystem for interdisciplinary collaboration, in addition to promoting discussion and stimulating new research hypotheses regarding pediatric pancreatic disorders. Oral presentations by experts in various fields of pancreatology led to thought-provoking discussion; in addition, a meet-the-professor luncheon stimulated critical evaluation of current research in pediatric pancreatic diseases, highlighting knowledge gaps and future research endeavors. The current report summarizes the major learning points from this novel symposium focusing on the growing demographic of pediatric pancreatic diseases.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.258
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2018
Admission routes1
Has abstractyes

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