Monitoring Child Growth and Development in Families at Risk of Stunting Using the Elsimil (Elektronik Siap Nikah dan Hamil) Application
Bibliographic record
Abstract
Bondowoso Regency have 14 priority communities by 2023 to accelerate stunting reduction, and Tamanan District is host to three of the fourteen villages. The objective of this community service is to implement the Elsimil application to track the growth and development of children from families at risk of stunting. This activity is an implementation of the Contextual Learning Model for Building Villages which integrated into the Pediatric Nursing Course. The team consists of 2 pediatric nursing lecturers and 34 nursing students. The methods used including monitoring children's growth and development, performing analyses, and educating families. Interviews, weight and height checks, developmental checks, and examination of family card records and KIA books are data collecting methods which then entered into the Elsimil program. This activity's population of interest is 31 families with children under the age of two in Tamanan District, devided into 3 villages: 9 children in Sumber Anom village, 11 children in Sumber Kemuning village, and the remaining 11 children in Kemirian village. This community service held in July-August 2023. Descriptive analysis is used in data analysis. Based on weight per age, 3.2% were severely underweight, 6.5% were underweight, 87.1% were normal weight, and 3.2% were at risk of being overweight. According to body length per age, 29% were severely stunted, 19.4% were short, and 51.6% were normal. A calculation of body weight per body length, 6.5% are extremely wasted, 3.2% are wasted, 64.5% are normal, 6.5% are at risk of being overweight, 3.2% are overweight, and 16.1% are obese. The results obtained based on body mass index per age were 3.2% severely wasted, 3.2% wasted, 64.5% good nutrition (normal), 16.1% at risk of overweight, 3.2% overweight, and 9.7% obesity. We conclude that this community service could optimize children monitoring and development by assisting stunted families through Elsimil application.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".