Impactos causados por metais em humanos devido à disposição inadequada de equipamentos eletroeletrônicos
Bibliographic record
Abstract
Os metais pesados podem acarretar serias disfuncoes na saude humana e causar graves problemas em plantas e animais. Este trabalho tem como objetivo desenvolver um estudo sobre o risco potencial que os residuos de equipamentos eletroeletronicos podem trazer para os seres humanos e o meio ambiente como um todo, devido a grande quantidade de metais pesados que estes possuem em sua composicao e, ao serem descartados de forma erronea, trazem preocupantes danos ao planeta. Analisando-se o potencial produtivo de microcomputadores pelos paises do BRICS (Brasil, Russia, India, China e Africa do Sul) e os paises do G7 (Estados Unidos, Japao, Alemanha, Reino Unido, Franca, Italia e Canada) em uma decada, no consumo de menor demanda ecologica de materia-prima e recursos naturais, sendo este de 3 computadores por decada, pretende-se observar a quantidade de metais pesados que podem ser produzidos nesse espaco de tempo por esses paises.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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; both teacher heads agree on what is shown here.
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".