Studi Optimasi IPAL Komunal Kota Malang dengan Pendekatan Model Stella
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hasil analisa kandungan bahan organik berupa Biological Oxygen Demand (BOD) dan Chemical Oxygen Demand (COD) pada badan air Sungai Brantas sebesar 92 mg/L dan 192 mg/L yang menandakan adanya pencemaran pada badan air disekitar IPAL Komunal. Kinerja IPAL Komunal yang belum optimal merupakan salah satu penyebab tingginya kandungan organik. Faktor tersebut dapat dioptimalkan menggunakan model Stella terhadap efluen IPAL Komunal dengan data kualitas influen serta fraksi removal unit pengolahan. Konfigurasi unit yang paling optimal diantara seluruh konfigurasi unit IPAL di Kota Malang yaitu tangki septik dan Anaerobic Baffle Reactor (ABR) dengan media filter dan waktu tinggal 28 jam. Hasil simulasi model Stella IPAL memiliki efisiensi removal terhadap BOD dan COD 100%, serta TSS 99% dengan debit influen 0.83 liter/detik.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it