Impact Of Chronic Arsenic Toxicity on Human Health- A Review
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
The levels of heavy metals in ground water continue to be higher than those considered acceptable by regulatory agencies in different countries across the world. One of the most important public health problems in the world is chronic arsenic poisoning, or arsenicosis, caused by drinking water that has been poisoned with arsenic. Arsenic poisoning over time has been related to a number of cancers of the skin, oral cavity, urinary bladder, kidney, and lung in addition to bone marrow depression, Blackfoot disease, cardiovascular disease, diabetes, hypertension, and a host of other ailments. In addition, arsenic causes DNA damage that has genotoxic effects. Around the world, 137 million people in 70 different nations depend on drinking water that has been drawn from severely contaminated groundwater. The two nations that have been affected the most so far are Bangladesh and West Bengal, India. The drinking water of 26 million people in nine districts of West Bengal contains levels of arsenic that are significantly higher than the WHO-acceptable limit of 10 g/l. The review focuses on the impact of chronic arsenic toxicity on public health worldwide.
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 | 0.046 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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