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Record W2014434179 · doi:10.1155/2009/518932

Comparison of Two Common Outpatient Preparations for Colonoscopy in Children and Youth

2009· article· en· W2014434179 on OpenAlexaff
Carolina Jiménez‐Rivera, Donna Haas, Margaret Boland, Janice Barkey, David R. Mack

Bibliographic record

VenueGastroenterology Research and Practice · 2009
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsMedicineColonoscopyTolerabilityCitric acidMagnesiumBowel preparationGastroenterologyOutpatient clinicSodium citrateInternal medicineGeneral surgeryAdverse effectColorectal cancerPathology

Abstract

fetched live from OpenAlex

Colonoscopies are often performed in children for diagnostic and therapeutic purposes. Our study compared two bowel-cleansing solutions: sodium picosulphate, magnesium oxide, and citric acid (Pico-Salax) with liquid magnesium citrate as preparations for colonoscopy. A retrospective chart review of all patients seen in the Gastroenterology outpatient clinic and who underwent bowel cleansing in preparation for colonoscopy from February to December 2006 was undertaken. Thirty-two children received Pico-Salax and 36 received liquid magnesium citrate. The tolerability of both solutions was similar. Most children in both groups had liquid stools and complete colonoscopies. Bowel preparation for a colonoscopy can be successfully achieved using either Pico-Salax or liquid magnesium citrate.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.095
GPT teacher head0.474
Teacher spread0.378 · 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 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

Citations24
Published2009
Admission routes1
Has abstractyes

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