From power to seafood safety: effects of global pollution on our children’s health
Bibliographic record
Abstract
Summary Mercury is a global pollutant and there is strong evidence that the emission will increase by 50% in 2050. The major source of mercury is from the emission of fuel fossil burning power plants. Mercury accumulates along the aquatic food chain and can reach high levels in fish and shellfish. Mercury is a known neurotoxicant that is particularly harmful to fetal brain development. However, fish and shellfish are widely available food that provides many nutrients, particularly the n-3 polyunsaturated fatty acids (n-3 PUFAs), to many populations globally and there are benefits linked to brain and visual system development in infants and reduced risk for certain forms of heart disease. International efforts are required to control the emission of mercury in the environment. Clear and concise messages on benefits and risks associated with fish consumption choices are required for the general public. Dall’energia alla sicurezza dei prodotti ittici: effetti dell’inquinamento globale sulla salute dei nostri bambini Riassunto Il mercurio e un inquinante globale e vi e una forte evidenza che le sue emissioni aumenteranno del 50% nel 2050. La principale fonte di mercurio proviene dall’emissione di impianti che bruciano combustibili fossili. Il mercurio si accumula lungo la catena alimentare acquatica e puo raggiungere livelli elevati in pesci e crostacei. Questo elemento e un noto neurotossico particolarmente dannoso per lo sviluppo fetale del cervello. Tuttavia, pesci e crostacei sono alimenti ampiamente disponibili che forniscono numerose sostanze nutrienti a molte popolazioni nel mondo, in particolare gli n-3 acidi grassi polinsaturi (n-3 PUFA) che apportano benefici correlati alla sviluppo del cervello e del sistema visivo nei neonati e un rischio ridotto per alcune forme di malattie cardiache. Gli sforzi internazionali hanno l’obbligo di controllo delle emissioni di mercurio nell’ambiente. Sono necessari messaggi chiari e concisi per il grande pubblico riguardo ai benefici e ai rischi associati al consumo di prodotti della pesca.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".