ANALISIS PERBANDINGAN DEBIT PADA DAS CIMANUK-COPONG KABUPATEN GARUT AKIBAT PERUBAHAN TATA GUNA LAHAN
Bibliographic record
Abstract
The transformation of land into cities to meet the needs of urban infrastructure is happening fast. As a result, the hydrological pattern changes, such as land that previously absorbed water slowly becomes less able to absorb water. The area of the Cimanuk-Copong watershed is 469.11 km^2. Comparative analysis of discharge in the Cimanuk-Copong watershed due to changes in land use is the key to identifying changes in river flow and their impact on the environment using the NRECA (National Rural Electric Cooperative Association) model, then the results of this calculation are calibrated. The results of the analysis of the comparison value of the average flow rate in the past (2003-2012) were 9.23 m^3/s, while the present (2013-2021) is 19.81 m^3/s. The results of the calibration of the efficiency coefficient value of the Nash-Sutcliffe (NSE) model of the Cimanuk-Copong DAS are 0.61663 including 0.36
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".