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Record W2799907907 · doi:10.1093/pch/pxx214

Paediatric type 1 diabetes 2018: Clinical and research insights

2018· article· en· W2799907907 on OpenAlexaff
Stephen Zborovski, Farid H. Mahmud

Bibliographic record

VenuePaediatrics & Child Health · 2018
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsType 2 diabetesMedicineDiabetes mellitusIntensive care medicineEndocrinology

Abstract

fetched live from OpenAlex

The management of children and adolescents with type 1 diabetes continues to progress as clinical and technological innovations enter into practice. Variability in glucose readings can present a significant challenge for care providers, patients and families alike and recent research demonstrates that insulin selection and site-related lipohypertrophy can significantly influence blood glucose levels. New technology aims to improve both glycemic control and quality of life. New insulin analogues have been developed and insulin pumps and continuous glucose monitoring systems continue to evolve toward a fully closed-loop system. While such systems are not yet currently available, incremental features such as 'low glucose suspend' are offered. As well, glucose sensors are now available that can be used for insulin dosing while reducing the number of capillary blood sugar checks. This review aims to provide the clinician with an overview of some of these latest aspects of diabetes care for children and adolescents.

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)0.002
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: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.079
GPT teacher head0.416
Teacher spread0.337 · 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
GenreReview

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

Citations1
Published2018
Admission routes1
Has abstractyes

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