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Record W3161005689 · doi:10.33368/inajoh.v0i0.23

Karakteristik pada Obesitas Berdasarkan Rentan Umur di Kelurahan Nganganaumala Kota Bau-Bau

2021· article· en· W3161005689 on OpenAlexaboutno aff
Armanto Makmun, Indri Meliawati Radisu

Bibliographic record

VenueIndonesian Journal of Health · 2021
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsUnderweightOverweightObesityMedicineIncidence (geometry)DemographyGerontologyEnvironmental health

Abstract

fetched live from OpenAlex

Background and Purpose: Obesity is an imbalance in the amount of food intake compared toenergy expenditure carried out by the body. Some of the factors that cause obesity include lifestyle,diet, and physical activity. Obesity in adulthood has an impact on health, where weight gain andobesity are risk factors for increasing the incidence of non-communicable diseases. The purpose ofthis study was to determine the relationship between age vulnerability and the incidence of obesity.Methods: This study is a descriptive research design. Data collected using a questionnaire. The dataof this study were categorical variables from 2 groups so that it used the Chi-Square test. Referencesearch results are entered into the Mendeley app using the system Vancouver. Results: The totalsample size of 98 people with adolescence 11-19 years 7 people (7.1%), adults 20-60 years 88 people(89.8%), elderly> 60 years 3 people (3.2%) . Based on gender, it was found that 18 men (18.4%) and80 women 81.6%). And based on BMI, it was found that 19 people were underweight (19.4%), normal41 people (41.8%), overweight 12 people (12.2%), obese 1 23 people (23.5%), and obese 2 3 people(3.1%). Conclusion: There is no relationship between age susceptibility to obesity.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.243
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.025
GPT teacher head0.316
Teacher spread0.291 · 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 teacher head, 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

Citations3
Published2021
Admission routes1
Has abstractyes

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