Estimativa do desperdício de metais pesados advindos do descarte de equipamentos eletroeletrônicos nos países do G7 e do BRICS
Bibliographic record
Abstract
Os metais pesados se configuram como um grave risco a saude humana e ao equilibrio ambiental, tendo em vista o seu potencial impactante e a caracteristica de bioacumular na teia trofica, gerando danos aos organismos vivos de topo de cadeia. Os eletroeletronicos possuem esses elementos na sua composicao, porem o mercado nao repassa essa informacao aos consumidores. Por outro lado, o estimulo excessivo para o consumo faz com que haja uma velocidade de compra e troca de equipamentos eletroeletronicos por causa de novos modelos ou sistemas operacionais. Realizou-se um estudo estimativo e comparativo do potencial produtivo de residuos de equipamentos eletroeletronicos entre os paises do G7 (Estados Unidos, Japao, Alemanha, Reino Unido, Franca, Italia e Canada) e do Brics (Brasil, Russia, India, China e Africa do Sul), em uma decada, sob a otica do consumo, consumo sustentavel e consumerismo. Dados secundarios foram analisados, percebendo-se que a quantidade desses residuos produzida nao se relaciona diretamente com o tamanho da populacao de um pais, mas com o modelo de consumo estimulado pela economia de cada pais.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".