KADAR HEMOGLOBIN PADA AKSEPTOR KB IUD
Bibliographic record
Abstract
The IUD is one of the most effective long-term use methods of contraception but has a side effect ofincreased menstrual blood volume. The purpose of this study was to determine whether there is arelationship between the length of use of IUD against hemoglobin levels. The design of this research isanalytic correlation with cross sectional approach. Population of 49 AKDR acceptors in PandanwangiVillage Working Area Puskesmas Pandanwangi Malang. The number of samples were 33 respondents.Sampling using stratified random sampling. Data collection uses observation sheets and hemoglobinlevels checks using the GCHb Easy Touch digital stick via home visits. Analysis of this research datausing Spearman Rank Correlation. Based on statistical test with α = 0,05 got value of r counted -0,531with value ρ value 0,023 (ρ = <0,05) which means that Ho rejected means there is relationship betweenlong use of Intrauterine Contraception (IUD) to Hemoglobin Level. Therefore, women with an anemictendency are not advised to use the IUD contraceptive method.Keywords: Duration of IUD Use, Hemoglobin Level
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".