THE RELATIONSHIP OF NUTRITIONAL STATUS WITH CRUDE MOTOR DEVELOPMENT IN CHILDREN AGED 2-3 YEARS IN POSYANDU WORK AREA SITU UDIK PUSKESMAS
Bibliographic record
Abstract
According to UNICEF in 2011,dataofthe high number ofgrowth and development disorderinchildren under fivewas obtained,especially motor development disorder where (27.5%) or 3 million children had disorder. This research aims to determine theCorrelation ofNutritional StatusandGross Motor Developmentin 2-3 Year OldChildren atMaternal and Child Health Servicein Situ UdikCommunity Health Center Working Area. This is an analytic researchwith cross-sectional research design. This research was conducted atMaternal and Child Health Service atSitu UdikCommunity Health CenterinOctober 2017-October 2018 with total sample of 114 2-3 year oldchildrenby implementingSlovin formula for the sampling. The instruments used weredemographic questionnaire, DDST IIobservation sheet, and weight scale that had been provided. Furthermore,univariate and bivariate analysis were applied in analyzing the data. Based on nutritional status,children who hadmalnutrition were 22 children (29.7%) with normal motor development, 43 children (58.1%) were suspected abnormal motor development, and 9 children (12.2%) who could not be tested. Children who hadgood nutrition were 21 children (56.8%) with normal gross motor development, 10 children (27.0%) were suspected, and 6 children (16.2%) who could not be tested. Children who hadovernutrition were 2 children (66.7%) with normal gross motor development, 1 (33.3%) child were suspected abnormal motor development. In addition, the statistical test value = 0.026 obtained meaning thatnutritional status has significant correlation withgross motor development in 2-3 year oldchildren atMaternal and Child Health Service in Situ Udik Community Health Center Working Area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".