Variasi Ketebalan Arang Cangkang Biji Karet dengan Metode Filtrasi Downflow Dalam Penurunan Parameter Fe Air Tanah Dalam
Bibliographic record
Abstract
Water resources generally cover surface and ground water. Surface water will be more easily polluted than ground water, because surface water is more easily contaminated with sources of pollution so that people use water sourced from deep ground water. In Jambi city particular the Kenali Asam Atas area, is included in a residential area with a moderate density of approximately ± 6,903 Ha. PDAM service area coverage is still 2%, from the service area coverage of 10965 SR. The purpose of this study was to reduce Fe and pH parameters in deep groundwater using downflow and aeration filtration methods on variations in thickness of rubber seed shell charcoal by filtration method and variation of processing time in the aeration process using bubble aerator. The results of the downflow filtration method using variations in the thickness of 15 cm and 30 cm rubber seed shell charcoal for Fe parameters of 0.302 mg / l and pH of 5.08, while in the aeration treatment process using a variation of processing time of 30 minutes and 60 minutes for Fe parameters amounting to 0.354 mg / l and pH of 5.23.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".