Lead Pollution in the Angke KapukMangrove Forest of the Jakarta Bay Area
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
Marine tourism is authorized in Jakarta Bay’s Angke Kapuk mangrove forest. Maritime vessel activities, maintenance, and land reclamation can pollute nearby aquatic environments and sedimentary deposits. This study examines lead (Pb), a heavy metal, in water and sediment samples to measure contamination. Lead pollution in aquatic habitats can harm aquatic organisms and humans through bioaccumulation in the food chain. The sampling was done twice in August 2023, seven days apart. This technique was done at three stations with different activities. Microwave Plasma-Atomic Emission Spectroscopy (MP-AES) was used to measure lead amounts in the samples. The water sample analysis showed 0.0022-0.0092 mg/L, matching Indonesian Government Regulation No. 22 of 2021 standards. Conversely, sediment samples showed 0.067-0.200 mg/kg, which is below the quality criteria set by ANZECC&ARMCANZ in 2000 for Australia and New Zealand and CCME in 2001 for Canada. Despite low pollution according to recognized criteria, heavy metals in ecotourism zones require government and public attention. Additional information, in-depth research on water contamination, and heightened awareness of the impacts of heavy metals may be necessary.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it