Analysis of model-based PM2.5 emission factors for on-road mobile sources in Mexico
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Se investigan los resultados del empleo del modelo US-EPA MOVES2010a para calcular los factores de emisin del parque vehicular mexicano, y se comparan dichos resultados con las estimaciones del Inventario Nacional de Emisiones de Mxico (INEM) de 2005. El estudio muestra que los factores de emisin PM2.5 basados en modelos, actualizados a partir de estudios recientes, pueden tener un impacto significativo en la estimacin de emisiones de PM2.5 procedentes de fuentes mviles en Mxico. Porcentajes mayores de vehculos antiguos tienden a incrementar las estimaciones de emisiones PM2.5 cuando se utiliza el modelo MOVES2010a en comparacin con las del INEM 2005; sin embargo, el impacto global sobre las emisiones de material particulado vara segn la cantidad y antigedad de los vehculos, y de acuerdo con los porcentajes de vehculos antiguos impulsados por diesel y gasolina en el parque vehicular de cada entidad federativa. Los resultados tambin indican que las estimaciones de PM2.5 con MOVES2010a fueron particularmente sensibles a la velocidad vehicular, la temperatura ambiente y el contenido de azufre, pero no a la humedad relativa. Hay una gran necesidad de comprender las caractersticas
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it