Green analysis impact in the determination of iron (Fe) against validation on well water
Bibliographic record
Abstract
The application of green analysis in the determination of Fe is done by minimizing the amount of material from the standard method (SNI-6989-4-2009) to half, a quarter, and a fifth part. The iron (Fe) test results obtained according to the standard, half, quarter and one-fifth methods respectively were 0.2098; 0.2418; 0.2194; and 0.2080 ppm. These results indicate that well water is safe for consumption because it is below the threshold determined by the Regulation of the Minister of Health of the Republic of Indonesia No. 492 of 2010. Validation of atomic absorption spectrophotometer (SSA) method for determining iron content (Fe) which includes linearity, Limit of Detection (LOD), Limit of Quantification (LOQ), precision, and accuracy shows good results for all variations in composition because following quality control requirements that exist in the standard method. But the one-way ANOVA test results for the four variations showed a significant difference. Composition following standard methods and one-fifth of the parts showed no different results. Whereas the variation in the composition of half and a quarter showed different results from the composition of standard testing. This is due to the composition of half and a quarter parts, the amount of HNO3 used is not integers (in decimal numbers) so that it affects the accuracy of the amount taken.
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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 | 0.000 |
| 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".