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Record W4404567318 · doi:10.2337/figshare.27610194.v1

<b>Designing a Structured Insulin Pump Program Pathway and Reducing Wait Times in the Diabetes Clinic at BC Children’s Hospital</b>

2024· preprint· en· W4404567318 on OpenAlexaboutno aff
Fatema S. Abdulhussein, Sanjukta Basak, Hannah Breadon, Erica Vance, Jillian Creagh, Sharleen Herrmann, Shazhan Amed

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachTelehealthEthnically diverseMedicineDiabetes mellitusTelemedicinePopulationFamily medicineNursingGerontologyHealth careEnvironmental healthEndocrinologyPolitical science

Abstract

fetched live from OpenAlex

BC Children’s Hospital (BCCH) is the only tertiary care, academic children’s hospital in the province of British Columbia, located in Vancouver, Canada. The pediatric diabetes clinic provides in-person and telehealth services to a large, ethnically diverse pediatric population living with diabetes across the province in urban and rural communities. It also has a diabetes telemedicine outreach program that involves BCCH endocrinologists partnering with local care teams to allow individuals to access a diabetes care provider virtually, while remaining closer to home.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.890
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0720.010

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 head0.015
GPT teacher head0.283
Teacher spread0.268 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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