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Record W2400308 · doi:10.18043/ncm.65.6.335

Diabetes Awareness among African Americans in Rural North Carolina

2004· article· en· W2400308 on OpenAlexaboutno aff
Angela K. Antony, Walid A. Baaklini

Bibliographic record

VenueNorth Carolina Medical Journal · 2004
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsnot available
Fundersnot available
KeywordsDiabetes mellitusMedicineGerontologyPublic healthSouth carolinaPopulationFamily medicineBehavioral Risk Factor Surveillance SystemDemographyHealth careEnvironmental healthNursingPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the extent of diabetes unawareness in rural North Carolina. METHODS: Randomly administered an eight-question survey to African Americans age 15-74 living in Halifax County North Carolina. RESULTS: Ninety-five out of 116 eligible participants completed the survey (82% response rate). Most (67%) of the participants reported having two or more major risk factors for Type II diabetes (diabetes mellitus). More than half (51.6%) of the participants were obese. Most (96.8%) of the participants reported having been tested for diabetes at some point in their lives (10% testedpositive, only 8.4% of the remaining 9o% reported ever having a second test). CONCLUSION: Diabetes mellitus is a very prevalentproblem among the African American population of Halifax County North Carolina. Our study underscores the fact that patients are not systematically screened and followed-up for diabetes melitus. More healthcare and commnity programs need to be adapted to fight this serious public health problem.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.187
Threshold uncertainty score0.372

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.268
Teacher spread0.255 · 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
Published2004
Admission routes1
Has abstractyes

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