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Record W7095159379

Costs of Diabetes Mellitus in Korea

2013· article· en· W7095159379 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies of British Isles
Canadian institutionsnot available
Fundersnot available
KeywordsDiabetes mellitusMedical expensesDiseaseMedical costsQuality of life (healthcare)Health careMedical careDisease managementType 2 diabetes
DOInot available

Abstract

fetched live from OpenAlex

Outcome research focusing on the economics of the medical field began in the mid-1990s and has included studies about costs, cost effectiveness, and policies. According to the American Diabetes Association, the total estimated cost of diabetes in 2007 was $174 billion. The economic burden of patients with diabetes in Canada is expected to be about $12.2 billion in 2010. Recent Korean studies have analyzed the expenses associated with type 2 diabetes for patients in selected general hospitals. Type 2 diabetic patients without complications cost approximately 1,184,563 won (the equivalent of US $1,184) per patient for healthcare annually. In contrast, patients with microvascular disease due to diabetic complications cost up to 4.7 times that amount, and patients with macrovascular disease incur up to 10.7 times the annual costs for patients without diabetic complications. Diabetic complications ultimately impact the quality of life for patients and patient mortality, and are associated with higher direct medical expenses for patients. To avoid increased medical costs, appropriate management techniques must be implemented to ensure timely care for patients with diabetes.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.016
GPT teacher head0.189
Teacher spread0.173 · 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
Published2013
Admission routes1
Has abstractyes

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