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Record W2891017674 · doi:10.1155/2018/5094569

Teens with Type 1 Diabetes: How Does Their Nutrition Measure Up?

2018· article· en· W2891017674 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Diabetes Research · 2018
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsUniversity of Toronto
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of Health
KeywordsMeasure (data warehouse)Type 2 diabetesType 1 diabetesDiabetes mellitusMedicineComputer scienceEndocrinologyData mining

Abstract

fetched live from OpenAlex

OBJECTIVE: To characterize the intake of macronutrient and fiber in adolescents with type 1 diabetes (T1D) and examine their association with health indicators. METHODS: = 257, mean age 12 ± 1.2 years, 49.4% girls) reported dietary intake via two separate 24-hour recall interviews during a two-week period. Demographic and medical variables were abstracted from questionnaires and medical charts. RESULTS: Controlling for demographic and diet variables, a higher percentage of daily energy intake from fats was associated with poorer HbA1c. In contrast, an association between higher percent of energy intake from proteins and carbohydrates was found with higher systolic and diastolic BP, respectively. CONCLUSIONS: Many early adolescents with T1D did not meet diabetes nutritional guidelines. Lower adherence to nutritional guidelines, specifically more than recommended energy intake from fats, was associated with poorer HbA1c. Addressing nutritional guidelines and increasing adherence as part of treatment may improve health outcomes for youth with T1D.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.376
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.065
GPT teacher head0.349
Teacher spread0.284 · 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