PERBEDAAN KADAR TRIGLISERIDA DARAH \nPADA PUASA 10 JAM DAN TANPA PUASA
Bibliographic record
Abstract
Background : The patient's preparation for triglyceride examination is still a matter of dispute, where there are two different opinions which state that fasting is recommended for triglyceride examination and there is no need for fasting for triglyceride examination. Several countries (Denmark, UK, Europe, Canada, Brazil, United States) and professional organizations such as the European Federation of Clinical Chemistry and Laboratory Medicine (ELFM, 2016); do not recommend fasting on triglyceride testing. Examination of triglycerides is recommended to fast in Indonesia before the examination of the Minister of Health Regulation No. 43 of 2013). \nTujuan : Knowing the results of the examination of blood triglyceride levels fasting 10 hours and without fasting. \nMethod : The type of research conducted is Analytical Observation by using one-static Group Comparison. The subjects of this study were students of DIV Medical Laboratory Technology Level 1, Level II, and Level III who were willing and had met the inclusion and exclusion criteria with total sampling technique. \nResults : The results of measuring triglyceride levels in fasting blood for 10 hours obtained an average result of 71.70 mg/dL and the results of measurements of triglyceride levels without fasting was 31.59 mg/dL. The results of these measurements were tested statistically and showed that there was no significant difference p=>0.05. \nConclusion : There is no difference in the results of examination of blood triglyceride levels fasting 10 hours and without fasting \nSuggestion: For further research, it is recommended to use a larger number of samples
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.062 | 0.018 |
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".