An exploratory analysis of hazardous substances registered in the Mexican Pollutant Releases and Transfers Register in the State of Tamaulipas
Bibliographic record
Abstract
The North American Free Trade Agreement required Mexico, the United States and Canada to measure pollutants released and transferred to the environment. In Mexico, the Ministry of Environment and Natural Resources publishes an annual report of pollutants released or transferred by public and private facilities across industrial sectors. Each facility must report substances listed in Official Mexican Standard NOM-165-SEMARNAT-2013. In this study, we used the SINAT tool to obtain records of pollutant releases by municipalities in the state of Tamaulipas. We preprocessed and analysed the substances released in Tamaulipas and mapped them to their corresponding groups based on monographs from the International Agency for Research on Cancer (IARC). These groupings were then used to identify toxic substances—such as benzene, arsenic and asbestos—classified as carcinogenic to humans (Group 1) in Tamaulipas.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".