Peran Kader Posyandu dalam Upaya Pencegahan Stunting pada Ibu Badutadi Kabupaten Tanjung Jabung Timur
Bibliographic record
Abstract
Hindering is a state of inability to flourish in youngsters under five years of age (babies under 5 years of age) which is brought about by tenacious lack of healthy sustenance so the kid is excessively short for his age. Lack of healthy sustenance happens when the child is in the belly and toward the start of the child's introduction to the world, however hindering most actually shows up after the youngster is two years of age. In view of SSGI records for 2021, it is known that in Jambi Territory the most elevated frequency of hindering is in Muaro Jambi Rule (27.2%) and the least is in Jambi City, for East Tanjung Jabung Regime it is 25.6%, better than the benefit of Jambi Area (22.4%). This examination is a quantitative exploration with a sectional methodology. The Geragai District served as the location of the research area. The ideal opportunity for leading the examination was in December 2022 with a populace of 574 moms with Baduta youngsters (old 0-23 months) and an example of 132. A progression of accounts utilizing a poll were then examined univariately, bivariately and multivariately utilizing chi-square. In view of the examination results, there is a connection between the job of posyandu units with a p-worth of 0.000 on forestalling hindering by female youngsters in East Tanjung Jabung Rule in 2022.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".