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Record W4254514599 · doi:10.24124/2008/bpgub526

Utilization of resources by parents of children with type 1 diabetes mellitus in the Prince George area.

2008· dissertation· en· W4254514599 on OpenAlexafffundabout
Kornelia Friedrich

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsLibrary and Archives Canada
FundersUniversity of Northern British Columbia
KeywordsGeorge (robot)Face (sociological concept)Diabetes mellitusMedicineDiseaseType 1 diabetesType 2 diabetesFamily medicinePsychologyNursingGerontologyEndocrinologyComputer scienceSociology

Abstract

fetched live from OpenAlex

Diabetes is a complex disease affecting many people. Parents of children with type 1 diabetes face many difficulties requiring numerous resources to help them cope. It is the utilization of various resources that can help to slow or prevent the onset of complications. This descriptive study explores the resources used by parents and their satisfaction with these resources. A survey was sent to 60 parents of children with type 1 diabetes. Twenty-seven were completed and returned. The children were listed at the Prince George Diabetes Clinic (PGDC). Overall, most parents indicated they used the PGDC and their pediatrician and are satisfied with these services, although wait times are a source of dissatisfaction. Family doctors and schools are not seen to possess the awareness or skills necessary to deal with situations that arise. Issues of need for financial help with diabetes supplies, and support for dealing with behaviour and emotional issues of children, particularly teenagers were commonly mentioned. Yet, expressed desires for support groups, youth camps or other services were mixed. --P.iii.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.975
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.285
Teacher spread0.265 · 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

Citations1
Published2008
Admission routes3
Has abstractyes

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