Neurosensory effects of chronic exposure to arsenic via drinking water in Inner Mongolia: I. signs, symptoms and pinprick testing
Bibliographic record
Abstract
This study was designed to assess the effects of exposure to arsenic in drinking water on neurosensory function. A questionnaire including neurological signs and symptoms and a brief neurological exam consisting of pinprick testing of the arms and legs and knee-jerk test were administered to 321 residents of the Bamen region of Inner Mongolia, China. Arsenic in water was measured by hydride generation atomic fluorescence. Participants were divided into three exposure groups--low (non-detectible-20), medium (100-300) and high (400-700 microg/I) arsenic. Significant group differences were observed in pinprick scores for all four limbs. Results indicate that arsenic alters pinprick (pain) thresholds at well-water concentrations as low as 400 microg/l, well below the 1000 microg/l threshold for neurological effect specified by NRC (1999). Regression models suggest that a 50% increase in pinprick score is associated with a 71-159 ppb increase in arsenic concentration.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".