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Record W2096591002 · doi:10.2337/dc07-2247

Evaluation of a Systems Navigator Model for Transition From Pediatric to Adult Care for Young Adults With Type 1 Diabetes

2008· article· en· W2096591002 on OpenAlexaff
Norma Van Walleghem, Catherine MacDonald, Heather Dean

Bibliographic record

VenueDiabetes Care · 2008
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversity of ManitobaWinnipeg Regional Health Authority
Fundersnot available
KeywordsMedicineAdult careYoung adultDiabetes mellitusMedical careHealth careTransitional careMEDLINEPediatricsGerontologyFamily medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine whether a systems navigator service, The Maestro Project, could increase medical surveillance for young adults with type 1 diabetes who transfer from pediatric to adult care. RESEARCH DESIGN AND METHODS: There were two cohorts of participants: 1) a younger group (aged 18 years, n = 82) who had the assistance of the navigator as they graduated from pediatric care and 2) an older group (aged 19-25 years) who were transferred to adult care without this initial support but later enrolled in the program. RESULTS: Of the older group (who did not have initial access to the navigator), 40% dropped out of adult medical care, compared with a dropout rate of 11% for the younger group, who had access to the navigator at the time of transfer from pediatric care. CONCLUSIONS: The systems navigator helped improve medical surveillance for both groups, although there was no evidence of improved short-term medical outcomes.

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)0.006
metaresearch head score (Gemma)0.012
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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.056
GPT teacher head0.359
Teacher spread0.303 · 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

Citations246
Published2008
Admission routes1
Has abstractyes

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