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Record W3024030194 · doi:10.1097/mpg.0000000000002760

NASPGHAN Nutrition University (N2U)

2020· article· en· W3024030194 on OpenAlexaff
Catherine Larson‐Nath, Praveen S. Goday, Lauren Fiechtner, Nisha Mangalat, Sally Schwartz, Ann Scheimann, Timothy Sentongo, Justine Turner

Bibliographic record

VenueJournal of Pediatric Gastroenterology and Nutrition · 2020
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal disorders and treatments
Canadian institutionsUniversity of Alberta HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicinePediatric gastroenterologyHepatologyInternal medicineClinical nutritionFamily medicineGuidelineNutrition EducationGastroenterologyGerontologyPathology

Abstract

fetched live from OpenAlex

The North American Society of Pediatric Gastroenterology, Hepatology, and Nutrition (NASPGHAN) developed NASPGHAN Nutrition University (N2U) in 2012 to improve nutrition education for pediatric gastroenterology providers. A total of 543 providers (physicians, registered dietitians, and advanced practice nurses) have applied to N2U and 285 have attended this 2-day course. We used survey methodology to compare attendees to applicants who did not attend. Course attendees reported more confidence than nonattendees in the nutritional management of patients with short bowel syndrome, feeding disorders, and gastrointestinal allergies, even though they were seen at similar frequency in both groups. Eighty-eight percent of attendees disseminated the information they learned at N2U through venues such as grand rounds or guideline/policy development. These results demonstrate the benefit of N2U in enhancing nutrition education for pediatric gastroenterology practitioners.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.045
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.004

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 head0.013
GPT teacher head0.218
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2020
Admission routes1
Has abstractyes

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