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Record W4301956237 · doi:10.1136/adc.86.suppl_1.a21

Gastroenterology, hepatology, and nutrition

2002· article· en· W4301956237 on OpenAlexaff

Bibliographic record

VenueArchives of Disease in Childhood · 2002
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineHepatologyInternal medicineGastroenterologyPediatric gastroenterology

Abstract

fetched live from OpenAlex

Aim: In addition to acid gastro-oesophageal reflux (GOR), non-acid GOR (pH > 4) may be clinically relevant in neurologically impaired children.However, standard pH metry can only detect the former.The aim of this study was to quantify acid and non-acid reflux in a group of these patients using a new catheter-related technique.Methods: Ten children (9 cerebral palsy, 1 Trisomy 21) fed intragastrically underwent 12 hour studies of intra-oesophageal 6 channel impedance and dual channel pH monitoring.All patients were off medication influencing gastric pH.Recordings were analyzed for the frequency of acid and non-acid GOR and the height reached by the refluxate.Results: Three hundred and sixty nine reflux events were detected with the combined technique.One hundred and ninety one (51.8%)were non-acid events (mean pH 5.6) and of these 138 (72.2%) reached the uppermost (1) impedance channel.Of the 178 acid reflux events (mean pH 3.1), 81.5% reached the uppermost channel.Conclusions: Over half of reflux events in neurologically impaired children are non-acidic and therefore are missed using standard pH metry.Most of these refluxes reached the upper oesophagus.Simultaneous intraoesophageal impedance and pH measurements proves to add valuable information that may improve therapeutic management in this patient group.

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)0.000
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: none
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0290.006

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 head0.026
GPT teacher head0.323
Teacher spread0.297 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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