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Record W2076863712 · doi:10.1258/acb.2010.010062

Establishment of a paediatric age-related reference interval for the measurement of urinary total fractionated metanephrines

2010· article· en· W2076863712 on OpenAlexfundno aff
Alison Griffin, Paula O’Shea, Roland FitzGerald, G. Richard O’Connor, William Tormey

Bibliographic record

VenueAnnals of Clinical Biochemistry International Journal of Laboratory Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsnot available
FundersHospital for Sick Children
KeywordsMetanephrinesMetanephrineNormetanephrineChromatographyConfidence intervalChemistryUrineUrinary systemUrologyInternal medicineMedicineBiochemistry

Abstract

fetched live from OpenAlex

INTRODUCTION: Normetanephrine and metanephrine are intermediate metabolites of noradrenaline and adrenaline metabolism. To assess whether normetanephrine and metanephrine analysis may aid in the diagnosis of Neuroblastoma, a reference interval for these metabolites must first be established. AIM: The overall aim of this study was to establish a paediatric age-related reference interval for the measurement of total fractionated metanephrines. METHODS: A total of 267 urine samples were analysed following acid hydrolysis. This releases the metanephrines from their sulphate-bound metabolites. The samples were analysed using reverse phase high-performance liquid chromatography with electro-chemical detection on a Gilson automated sequential trace enrichment of dialysate sample system. RESULTS: Data were analysed using Minitab Release version 14. Outliers were removed using the Dixon/Reed one-third rule. Partitioning of the age groups was achieved using Harris and Boyd's standard normal deviate test. Non-parametric analysis of the data was performed, followed by the establishment of the 2.5th and the 97.5th reference limits. CONCLUSIONS: The established reference intervals are described in Table 2.

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)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.132
GPT teacher head0.453
Teacher spread0.321 · 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.

Study designBench or experimental
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

Citations20
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of Clinical Biochemistry International Journal of Laboratory MedicineSame topicNeuroblastoma Research and TreatmentsFrench-language works237,207