Research Trends in Emerging Contaminants on the Aquatic Environments of Tanzania
Bibliographic record
Abstract
The continuity for discovery and production of new chemicals, allied products, and uses has currently resulted into generation of recent form of contaminants known as Emerging Contaminants (ECs). Once in the aquatic environment ECs are carcinogenic and cause other threats to both human's and animals' health. Due to their effects this study was aimed at investigating research trends of ECs in Tanzania. Findings revealed that USA and EU countries were leading in ECs researches, little followed by Asia, South Africa, and then Zambia. Only few guidelines from USA-EPA, WHO, Canada, and Australia existed. Neither published guidelines nor regulations for ECs existed in Tanzania; rather only the occurrence of some disinfection by-products and antibiotics was, respectively, reported in Arusha and Dar es Salaam, Tanzania. As these reports had a limited coverage of ECs, henceforth, these findings constitute the first-line reference materials for ECs research in Tanzania which shall be useful for future monitoring and regulation planning.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".